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aio-base.owl
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<?xml version="1.0"?>
<rdf:RDF xmlns="https://w3id.org/aio/aio-base.owl#"
xml:base="https://w3id.org/aio/aio-base.owl"
xmlns:dc="http://purl.org/dc/elements/1.1/"
xmlns:BFO="http://purl.obolibrary.org/obo/BFO_"
xmlns:IAO="http://purl.obolibrary.org/obo/IAO_"
xmlns:aio="https://w3id.org/aio/"
xmlns:obo="http://purl.obolibrary.org/obo/"
xmlns:owl="http://www.w3.org/2002/07/owl#"
xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"
xmlns:xml="http://www.w3.org/XML/1998/namespace"
xmlns:xsd="http://www.w3.org/2001/XMLSchema#"
xmlns:rdfs="http://www.w3.org/2000/01/rdf-schema#"
xmlns:dcterms="http://purl.org/dc/terms/"
xmlns:oboInOwl="http://www.geneontology.org/formats/oboInOwl#">
<owl:Ontology rdf:about="https://w3id.org/aio/aio-base.owl">
<owl:versionIRI rdf:resource="https://w3id.org/aio/releases/2024-11-11/aio-base.owl"/>
<dc:type rdf:resource="http://purl.obolibrary.org/obo/IAO_8000001"/>
<dcterms:description>This ontology models classes and relationships describing deep learning networks, their component layers and activation functions, as well as potential biases.</dcterms:description>
<dcterms:license rdf:resource="http://creativecommons.org/licenses/by/4.0/"/>
<dcterms:title>Artificial Intelligence Ontology</dcterms:title>
<owl:versionInfo>2024-11-11</owl:versionInfo>
</owl:Ontology>
<!--
///////////////////////////////////////////////////////////////////////////////////////
//
// Annotation properties
//
///////////////////////////////////////////////////////////////////////////////////////
-->
<!-- http://purl.obolibrary.org/obo/IAO_0000115 -->
<owl:AnnotationProperty rdf:about="http://purl.obolibrary.org/obo/IAO_0000115"/>
<!-- http://purl.org/dc/elements/1.1/type -->
<owl:AnnotationProperty rdf:about="http://purl.org/dc/elements/1.1/type"/>
<!-- http://purl.org/dc/terms/description -->
<owl:AnnotationProperty rdf:about="http://purl.org/dc/terms/description"/>
<!-- http://purl.org/dc/terms/license -->
<owl:AnnotationProperty rdf:about="http://purl.org/dc/terms/license"/>
<!-- http://purl.org/dc/terms/title -->
<owl:AnnotationProperty rdf:about="http://purl.org/dc/terms/title"/>
<!-- http://www.geneontology.org/formats/oboInOwl#SubsetProperty -->
<owl:AnnotationProperty rdf:about="http://www.geneontology.org/formats/oboInOwl#SubsetProperty"/>
<!-- http://www.geneontology.org/formats/oboInOwl#hasDbXref -->
<owl:AnnotationProperty rdf:about="http://www.geneontology.org/formats/oboInOwl#hasDbXref"/>
<!-- http://www.geneontology.org/formats/oboInOwl#hasExactSynonym -->
<owl:AnnotationProperty rdf:about="http://www.geneontology.org/formats/oboInOwl#hasExactSynonym"/>
<!-- http://www.geneontology.org/formats/oboInOwl#hasRelatedSynonym -->
<owl:AnnotationProperty rdf:about="http://www.geneontology.org/formats/oboInOwl#hasRelatedSynonym"/>
<!-- http://www.geneontology.org/formats/oboInOwl#inSubset -->
<owl:AnnotationProperty rdf:about="http://www.geneontology.org/formats/oboInOwl#inSubset"/>
<!-- https://w3id.org/aio/ActivationFunctionSubset -->
<owl:AnnotationProperty rdf:about="https://w3id.org/aio/ActivationFunctionSubset">
<rdfs:comment>Activation Function Subset</rdfs:comment>
<rdfs:subPropertyOf rdf:resource="http://www.geneontology.org/formats/oboInOwl#SubsetProperty"/>
</owl:AnnotationProperty>
<!-- https://w3id.org/aio/BiasSubset -->
<owl:AnnotationProperty rdf:about="https://w3id.org/aio/BiasSubset">
<rdfs:comment xml:lang="en">Bias Subset</rdfs:comment>
<rdfs:subPropertyOf rdf:resource="http://www.geneontology.org/formats/oboInOwl#SubsetProperty"/>
</owl:AnnotationProperty>
<!-- https://w3id.org/aio/ClassSubset -->
<owl:AnnotationProperty rdf:about="https://w3id.org/aio/ClassSubset">
<rdfs:comment xml:lang="en">Class Subset</rdfs:comment>
<rdfs:subPropertyOf rdf:resource="http://www.geneontology.org/formats/oboInOwl#SubsetProperty"/>
</owl:AnnotationProperty>
<!-- https://w3id.org/aio/FunctionSubset -->
<owl:AnnotationProperty rdf:about="https://w3id.org/aio/FunctionSubset">
<rdfs:comment xml:lang="en">Function Subset</rdfs:comment>
<rdfs:subPropertyOf rdf:resource="http://www.geneontology.org/formats/oboInOwl#SubsetProperty"/>
</owl:AnnotationProperty>
<!-- https://w3id.org/aio/InstanceNormalizationLayerSubset -->
<owl:AnnotationProperty rdf:about="https://w3id.org/aio/InstanceNormalizationLayerSubset">
<rdfs:comment>Instance Normalization Layer Subset</rdfs:comment>
<rdfs:subPropertyOf rdf:resource="http://www.geneontology.org/formats/oboInOwl#SubsetProperty"/>
</owl:AnnotationProperty>
<!-- https://w3id.org/aio/LayerSubset -->
<owl:AnnotationProperty rdf:about="https://w3id.org/aio/LayerSubset">
<rdfs:comment xml:lang="en">Layer Subset</rdfs:comment>
<rdfs:subPropertyOf rdf:resource="http://www.geneontology.org/formats/oboInOwl#SubsetProperty"/>
</owl:AnnotationProperty>
<!-- https://w3id.org/aio/MachineLearningSubset -->
<owl:AnnotationProperty rdf:about="https://w3id.org/aio/MachineLearningSubset">
<rdfs:comment xml:lang="en">Machine Learning Subset</rdfs:comment>
<rdfs:subPropertyOf rdf:resource="http://www.geneontology.org/formats/oboInOwl#SubsetProperty"/>
</owl:AnnotationProperty>
<!-- https://w3id.org/aio/ModelSubset -->
<owl:AnnotationProperty rdf:about="https://w3id.org/aio/ModelSubset">
<rdfs:comment xml:lang="en">Model Subset</rdfs:comment>
<rdfs:subPropertyOf rdf:resource="http://www.geneontology.org/formats/oboInOwl#SubsetProperty"/>
</owl:AnnotationProperty>
<!-- https://w3id.org/aio/NetworkSubset -->
<owl:AnnotationProperty rdf:about="https://w3id.org/aio/NetworkSubset">
<rdfs:comment xml:lang="en">Network Subset</rdfs:comment>
<rdfs:subPropertyOf rdf:resource="http://www.geneontology.org/formats/oboInOwl#SubsetProperty"/>
</owl:AnnotationProperty>
<!-- https://w3id.org/aio/PreprocessingSubset -->
<owl:AnnotationProperty rdf:about="https://w3id.org/aio/PreprocessingSubset">
<rdfs:comment xml:lang="en">Preprocessing Subset</rdfs:comment>
<rdfs:subPropertyOf rdf:resource="http://www.geneontology.org/formats/oboInOwl#SubsetProperty"/>
</owl:AnnotationProperty>
<!--
///////////////////////////////////////////////////////////////////////////////////////
//
// Object Properties
//
///////////////////////////////////////////////////////////////////////////////////////
-->
<!-- http://purl.obolibrary.org/obo/BFO_0000051 -->
<owl:ObjectProperty rdf:about="http://purl.obolibrary.org/obo/BFO_0000051"/>
<!--
///////////////////////////////////////////////////////////////////////////////////////
//
// Classes
//
///////////////////////////////////////////////////////////////////////////////////////
-->
<!-- https://w3id.org/aio/AbstractRNNCell -->
<owl:Class rdf:about="https://w3id.org/aio/AbstractRNNCell">
<rdfs:subClassOf rdf:resource="https://w3id.org/aio/Layer"/>
<obo:IAO_0000115>A layer representing an RNN cell that is the base class for implementing RNN cells with custom behavior.</obo:IAO_0000115>
<oboInOwl:inSubset rdf:resource="https://w3id.org/aio/LayerSubset"/>
<rdfs:label>AbstractRNNCell</rdfs:label>
</owl:Class>
<owl:Axiom>
<owl:annotatedSource rdf:resource="https://w3id.org/aio/AbstractRNNCell"/>
<owl:annotatedProperty rdf:resource="http://purl.obolibrary.org/obo/IAO_0000115"/>
<owl:annotatedTarget>A layer representing an RNN cell that is the base class for implementing RNN cells with custom behavior.</owl:annotatedTarget>
<oboInOwl:hasDbXref rdf:resource="https://www.tensorflow.org/api_docs/python/tf/keras/layers/AbstractRNNCell"/>
</owl:Axiom>
<!-- https://w3id.org/aio/ActivationLayer -->
<owl:Class rdf:about="https://w3id.org/aio/ActivationLayer">
<rdfs:subClassOf rdf:resource="https://w3id.org/aio/Layer"/>
<obo:IAO_0000115>A layer that applies an activation function to an output.</obo:IAO_0000115>
<oboInOwl:inSubset rdf:resource="https://w3id.org/aio/LayerSubset"/>
<rdfs:comment>Applies an activation function to an output.</rdfs:comment>
<rdfs:label>Activation Layer</rdfs:label>
</owl:Class>
<owl:Axiom>
<owl:annotatedSource rdf:resource="https://w3id.org/aio/ActivationLayer"/>
<owl:annotatedProperty rdf:resource="http://purl.obolibrary.org/obo/IAO_0000115"/>
<owl:annotatedTarget>A layer that applies an activation function to an output.</owl:annotatedTarget>
<oboInOwl:hasDbXref rdf:resource="https://www.tensorflow.org/api_docs/python/tf/keras/layers/Activation"/>
</owl:Axiom>
<!-- https://w3id.org/aio/ActiveLearning -->
<owl:Class rdf:about="https://w3id.org/aio/ActiveLearning">
<rdfs:subClassOf rdf:resource="https://w3id.org/aio/MachineLearningTask"/>
<obo:IAO_0000115>A machine learning task focused on methods that interactively query a user or another information source to label new data points with the desired outputs.</obo:IAO_0000115>
<oboInOwl:hasExactSynonym>Query Learning</oboInOwl:hasExactSynonym>
<oboInOwl:inSubset rdf:resource="https://w3id.org/aio/MachineLearningSubset"/>
<rdfs:label>Active Learning</rdfs:label>
</owl:Class>
<owl:Axiom>
<owl:annotatedSource rdf:resource="https://w3id.org/aio/ActiveLearning"/>
<owl:annotatedProperty rdf:resource="http://purl.obolibrary.org/obo/IAO_0000115"/>
<owl:annotatedTarget>A machine learning task focused on methods that interactively query a user or another information source to label new data points with the desired outputs.</owl:annotatedTarget>
<oboInOwl:hasDbXref rdf:resource="https://en.wikipedia.org/wiki/Active_learning_(machine_learning)"/>
</owl:Axiom>
<!-- https://w3id.org/aio/ActivityBias -->
<owl:Class rdf:about="https://w3id.org/aio/ActivityBias">
<rdfs:subClassOf rdf:resource="https://w3id.org/aio/UseAndInterpretationBias"/>
<obo:IAO_0000115>A use and interpretation bias occurring when systems/platforms get training data from their most active users rather than less active or inactive users.</obo:IAO_0000115>
<oboInOwl:inSubset rdf:resource="https://w3id.org/aio/BiasSubset"/>
<rdfs:label>Activity Bias</rdfs:label>
</owl:Class>
<owl:Axiom>
<owl:annotatedSource rdf:resource="https://w3id.org/aio/ActivityBias"/>
<owl:annotatedProperty rdf:resource="http://purl.obolibrary.org/obo/IAO_0000115"/>
<owl:annotatedTarget>A use and interpretation bias occurring when systems/platforms get training data from their most active users rather than less active or inactive users.</owl:annotatedTarget>
<oboInOwl:hasDbXref rdf:resource="https://en.wikipedia.org/wiki/Interpretive_bias"/>
</owl:Axiom>
<!-- https://w3id.org/aio/ActivityRegularizationLayer -->
<owl:Class rdf:about="https://w3id.org/aio/ActivityRegularizationLayer">
<rdfs:subClassOf rdf:resource="https://w3id.org/aio/RegularizationLayer"/>
<obo:IAO_0000115>A regularization layer that applies an update to the cost function based on input activity.</obo:IAO_0000115>
<oboInOwl:inSubset rdf:resource="https://w3id.org/aio/LayerSubset"/>
<rdfs:label>ActivityRegularization Layer</rdfs:label>
</owl:Class>
<owl:Axiom>
<owl:annotatedSource rdf:resource="https://w3id.org/aio/ActivityRegularizationLayer"/>
<owl:annotatedProperty rdf:resource="http://purl.obolibrary.org/obo/IAO_0000115"/>
<owl:annotatedTarget>A regularization layer that applies an update to the cost function based on input activity.</owl:annotatedTarget>
<oboInOwl:hasDbXref rdf:resource="https://www.tensorflow.org/api_docs/python/tf/keras/layers/ActivityRegularization"/>
</owl:Axiom>
<!-- https://w3id.org/aio/AdaptiveAvgPool1DLayer -->
<owl:Class rdf:about="https://w3id.org/aio/AdaptiveAvgPool1DLayer">
<rdfs:subClassOf rdf:resource="https://w3id.org/aio/PoolingLayer"/>
<obo:IAO_0000115>A pooling layer that applies a 1D adaptive average pooling over an input signal composed of several input planes.</obo:IAO_0000115>
<oboInOwl:hasExactSynonym>AdaptiveAvgPool1D</oboInOwl:hasExactSynonym>
<oboInOwl:inSubset rdf:resource="https://w3id.org/aio/LayerSubset"/>
<rdfs:label>AdaptiveAvgPool1D Layer</rdfs:label>
</owl:Class>
<owl:Axiom>
<owl:annotatedSource rdf:resource="https://w3id.org/aio/AdaptiveAvgPool1DLayer"/>
<owl:annotatedProperty rdf:resource="http://purl.obolibrary.org/obo/IAO_0000115"/>
<owl:annotatedTarget>A pooling layer that applies a 1D adaptive average pooling over an input signal composed of several input planes.</owl:annotatedTarget>
<oboInOwl:hasDbXref rdf:resource="https://pytorch.org/docs/stable/nn.html#pooling-layers"/>
</owl:Axiom>
<!-- https://w3id.org/aio/AdaptiveAvgPool2DLayer -->
<owl:Class rdf:about="https://w3id.org/aio/AdaptiveAvgPool2DLayer">
<rdfs:subClassOf rdf:resource="https://w3id.org/aio/PoolingLayer"/>
<obo:IAO_0000115>A pooling layer that applies a 2D adaptive average pooling over an input signal composed of several input planes.</obo:IAO_0000115>
<oboInOwl:hasExactSynonym>AdaptiveAvgPool2D</oboInOwl:hasExactSynonym>
<oboInOwl:inSubset rdf:resource="https://w3id.org/aio/LayerSubset"/>
<rdfs:label>AdaptiveAvgPool2D Layer</rdfs:label>
</owl:Class>
<owl:Axiom>
<owl:annotatedSource rdf:resource="https://w3id.org/aio/AdaptiveAvgPool2DLayer"/>
<owl:annotatedProperty rdf:resource="http://purl.obolibrary.org/obo/IAO_0000115"/>
<owl:annotatedTarget>A pooling layer that applies a 2D adaptive average pooling over an input signal composed of several input planes.</owl:annotatedTarget>
<oboInOwl:hasDbXref rdf:resource="https://pytorch.org/docs/stable/nn.html#pooling-layers"/>
</owl:Axiom>
<!-- https://w3id.org/aio/AdaptiveAvgPool3DLayer -->
<owl:Class rdf:about="https://w3id.org/aio/AdaptiveAvgPool3DLayer">
<rdfs:subClassOf rdf:resource="https://w3id.org/aio/PoolingLayer"/>
<obo:IAO_0000115>A pooling layer that applies a 3D adaptive average pooling over an input signal composed of several input planes.</obo:IAO_0000115>
<oboInOwl:hasExactSynonym>AdaptiveAvgPool3D</oboInOwl:hasExactSynonym>
<oboInOwl:inSubset rdf:resource="https://w3id.org/aio/LayerSubset"/>
<rdfs:label>AdaptiveAvgPool3D Layer</rdfs:label>
</owl:Class>
<owl:Axiom>
<owl:annotatedSource rdf:resource="https://w3id.org/aio/AdaptiveAvgPool3DLayer"/>
<owl:annotatedProperty rdf:resource="http://purl.obolibrary.org/obo/IAO_0000115"/>
<owl:annotatedTarget>A pooling layer that applies a 3D adaptive average pooling over an input signal composed of several input planes.</owl:annotatedTarget>
<oboInOwl:hasDbXref rdf:resource="https://pytorch.org/docs/stable/nn.html#pooling-layers"/>
</owl:Axiom>
<!-- https://w3id.org/aio/AdaptiveMaxPool1DLayer -->
<owl:Class rdf:about="https://w3id.org/aio/AdaptiveMaxPool1DLayer">
<rdfs:subClassOf rdf:resource="https://w3id.org/aio/PoolingLayer"/>
<obo:IAO_0000115>A pooling layer that applies a 1D adaptive max pooling over an input signal composed of several input planes.</obo:IAO_0000115>
<oboInOwl:hasExactSynonym>AdaptiveMaxPool1D</oboInOwl:hasExactSynonym>
<oboInOwl:inSubset rdf:resource="https://w3id.org/aio/LayerSubset"/>
<rdfs:label>AdaptiveMaxPool1D Layer</rdfs:label>
</owl:Class>
<owl:Axiom>
<owl:annotatedSource rdf:resource="https://w3id.org/aio/AdaptiveMaxPool1DLayer"/>
<owl:annotatedProperty rdf:resource="http://purl.obolibrary.org/obo/IAO_0000115"/>
<owl:annotatedTarget>A pooling layer that applies a 1D adaptive max pooling over an input signal composed of several input planes.</owl:annotatedTarget>
<oboInOwl:hasDbXref rdf:resource="https://pytorch.org/docs/stable/nn.html#pooling-layers"/>
</owl:Axiom>
<!-- https://w3id.org/aio/AdaptiveMaxPool2DLayer -->
<owl:Class rdf:about="https://w3id.org/aio/AdaptiveMaxPool2DLayer">
<rdfs:subClassOf rdf:resource="https://w3id.org/aio/PoolingLayer"/>
<obo:IAO_0000115>A pooling layer that applies a 2D adaptive max pooling over an input signal composed of several input planes.</obo:IAO_0000115>
<oboInOwl:hasExactSynonym>AdaptiveMaxPool2D</oboInOwl:hasExactSynonym>
<oboInOwl:inSubset rdf:resource="https://w3id.org/aio/LayerSubset"/>
<rdfs:label>AdaptiveMaxPool2D Layer</rdfs:label>
</owl:Class>
<owl:Axiom>
<owl:annotatedSource rdf:resource="https://w3id.org/aio/AdaptiveMaxPool2DLayer"/>
<owl:annotatedProperty rdf:resource="http://purl.obolibrary.org/obo/IAO_0000115"/>
<owl:annotatedTarget>A pooling layer that applies a 2D adaptive max pooling over an input signal composed of several input planes.</owl:annotatedTarget>
<oboInOwl:hasDbXref rdf:resource="https://pytorch.org/docs/stable/nn.html#pooling-layers"/>
</owl:Axiom>
<!-- https://w3id.org/aio/AdaptiveMaxPool3DLayer -->
<owl:Class rdf:about="https://w3id.org/aio/AdaptiveMaxPool3DLayer">
<rdfs:subClassOf rdf:resource="https://w3id.org/aio/PoolingLayer"/>
<obo:IAO_0000115>A pooling layer that applies a 3D adaptive max pooling over an input signal composed of several input planes.</obo:IAO_0000115>
<oboInOwl:hasExactSynonym>AdaptiveMaxPool3D</oboInOwl:hasExactSynonym>
<oboInOwl:inSubset rdf:resource="https://w3id.org/aio/LayerSubset"/>
<rdfs:label>AdaptiveMaxPool3D Layer</rdfs:label>
</owl:Class>
<owl:Axiom>
<owl:annotatedSource rdf:resource="https://w3id.org/aio/AdaptiveMaxPool3DLayer"/>
<owl:annotatedProperty rdf:resource="http://purl.obolibrary.org/obo/IAO_0000115"/>
<owl:annotatedTarget>A pooling layer that applies a 3D adaptive max pooling over an input signal composed of several input planes.</owl:annotatedTarget>
<oboInOwl:hasDbXref rdf:resource="https://pytorch.org/docs/stable/nn.html#pooling-layers"/>
</owl:Axiom>
<!-- https://w3id.org/aio/AddLayer -->
<owl:Class rdf:about="https://w3id.org/aio/AddLayer">
<rdfs:subClassOf rdf:resource="https://w3id.org/aio/MergingLayer"/>
<obo:IAO_0000115>A merging layer that adds a list of inputs taking as input a list of tensors all of the same shape.</obo:IAO_0000115>
<oboInOwl:inSubset rdf:resource="https://w3id.org/aio/LayerSubset"/>
<rdfs:comment>Layer that adds a list of inputs. It takes as input a list of tensors, all of the same shape, and returns a single tensor (also of the same shape).</rdfs:comment>
<rdfs:label>Add Layer</rdfs:label>
</owl:Class>
<owl:Axiom>
<owl:annotatedSource rdf:resource="https://w3id.org/aio/AddLayer"/>
<owl:annotatedProperty rdf:resource="http://purl.obolibrary.org/obo/IAO_0000115"/>
<owl:annotatedTarget>A merging layer that adds a list of inputs taking as input a list of tensors all of the same shape.</owl:annotatedTarget>
<oboInOwl:hasDbXref rdf:resource="https://www.tensorflow.org/api_docs/python/tf/keras/layers/Add"/>
</owl:Axiom>
<!-- https://w3id.org/aio/AdditionLayer -->
<owl:Class rdf:about="https://w3id.org/aio/AdditionLayer">
<rdfs:subClassOf rdf:resource="https://w3id.org/aio/Layer"/>
<obo:IAO_0000115>A layer that adds inputs from one or more other layers to cells or neurons of a target layer.</obo:IAO_0000115>
<oboInOwl:inSubset rdf:resource="https://w3id.org/aio/LayerSubset"/>
<rdfs:label>Addition Layer</rdfs:label>
</owl:Class>
<!-- https://w3id.org/aio/AdditiveAttentionLayer -->
<owl:Class rdf:about="https://w3id.org/aio/AdditiveAttentionLayer">
<rdfs:subClassOf rdf:resource="https://w3id.org/aio/AttentionLayer"/>
<obo:IAO_0000115>An attention layer that implements additive attention also known as Bahdanau-style attention.</obo:IAO_0000115>
<oboInOwl:inSubset rdf:resource="https://w3id.org/aio/LayerSubset"/>
<rdfs:comment>Additive attention layer, a.k.a. Bahdanau-style attention.</rdfs:comment>
<rdfs:label>AdditiveAttention Layer</rdfs:label>
</owl:Class>
<owl:Axiom>
<owl:annotatedSource rdf:resource="https://w3id.org/aio/AdditiveAttentionLayer"/>
<owl:annotatedProperty rdf:resource="http://purl.obolibrary.org/obo/IAO_0000115"/>
<owl:annotatedTarget>An attention layer that implements additive attention also known as Bahdanau-style attention.</owl:annotatedTarget>
<oboInOwl:hasDbXref rdf:resource="https://www.tensorflow.org/api_docs/python/tf/keras/layers/AdditiveAttention"/>
</owl:Axiom>
<!-- https://w3id.org/aio/AlphaDropoutLayer -->
<owl:Class rdf:about="https://w3id.org/aio/AlphaDropoutLayer">
<rdfs:subClassOf rdf:resource="https://w3id.org/aio/RegularizationLayer"/>
<obo:IAO_0000115>A regularization layer that applies Alpha Dropout to the input keeping mean and variance of inputs to ensure self-normalizing property.</obo:IAO_0000115>
<oboInOwl:inSubset rdf:resource="https://w3id.org/aio/LayerSubset"/>
<rdfs:comment>Applies Alpha Dropout to the input. Alpha Dropout is a Dropout that keeps mean and variance of inputs to their original values, in order to ensure the self-normalizing property even after this dropout. Alpha Dropout fits well to Scaled Exponential Linear Units by randomly setting activations to the negative saturation value.</rdfs:comment>
<rdfs:label>AlphaDropout Layer</rdfs:label>
</owl:Class>
<owl:Axiom>
<owl:annotatedSource rdf:resource="https://w3id.org/aio/AlphaDropoutLayer"/>
<owl:annotatedProperty rdf:resource="http://purl.obolibrary.org/obo/IAO_0000115"/>
<owl:annotatedTarget>A regularization layer that applies Alpha Dropout to the input keeping mean and variance of inputs to ensure self-normalizing property.</owl:annotatedTarget>
<oboInOwl:hasDbXref rdf:resource="https://www.tensorflow.org/api_docs/python/tf/keras/layers/AlphaDropout"/>
</owl:Axiom>
<!-- https://w3id.org/aio/AmplificationBias -->
<owl:Class rdf:about="https://w3id.org/aio/AmplificationBias">
<rdfs:subClassOf rdf:resource="https://w3id.org/aio/ProcessingBias"/>
<obo:IAO_0000115>A processing bias arising when the distribution over prediction outputs is skewed compared to the prior distribution of the prediction target.</obo:IAO_0000115>
<oboInOwl:inSubset rdf:resource="https://w3id.org/aio/BiasSubset"/>
<rdfs:label>Amplification Bias</rdfs:label>
</owl:Class>
<owl:Axiom>
<owl:annotatedSource rdf:resource="https://w3id.org/aio/AmplificationBias"/>
<owl:annotatedProperty rdf:resource="http://purl.obolibrary.org/obo/IAO_0000115"/>
<owl:annotatedTarget>A processing bias arising when the distribution over prediction outputs is skewed compared to the prior distribution of the prediction target.</owl:annotatedTarget>
<oboInOwl:hasDbXref rdf:resource="https://royalsocietypublishing.org/doi/10.1098/rspb.2019.0165#d1e5237"/>
</owl:Axiom>
<!-- https://w3id.org/aio/AnchoringBias -->
<owl:Class rdf:about="https://w3id.org/aio/AnchoringBias">
<rdfs:subClassOf rdf:resource="https://w3id.org/aio/IndividualBias"/>
<obo:IAO_0000115>An individual bias characterized by the influence of a reference point or anchor on decisions leading to insufficient adjustment from that anchor point.</obo:IAO_0000115>
<oboInOwl:inSubset rdf:resource="https://w3id.org/aio/BiasSubset"/>
<rdfs:label>Anchoring Bias</rdfs:label>
</owl:Class>
<owl:Axiom>
<owl:annotatedSource rdf:resource="https://w3id.org/aio/AnchoringBias"/>
<owl:annotatedProperty rdf:resource="http://purl.obolibrary.org/obo/IAO_0000115"/>
<owl:annotatedTarget>An individual bias characterized by the influence of a reference point or anchor on decisions leading to insufficient adjustment from that anchor point.</owl:annotatedTarget>
<oboInOwl:hasDbXref rdf:resource="https://doi.org/10.6028/NIST.SP.1270"/>
</owl:Axiom>
<!-- https://w3id.org/aio/AnnotatorReportingBias -->
<owl:Class rdf:about="https://w3id.org/aio/AnnotatorReportingBias">
<rdfs:subClassOf rdf:resource="https://w3id.org/aio/IndividualBias"/>
<obo:IAO_0000115>An individual bias occurring when users rely on automation as a heuristic replacement for their own information seeking and processing.</obo:IAO_0000115>
<oboInOwl:inSubset rdf:resource="https://w3id.org/aio/BiasSubset"/>
<rdfs:label>Annotator Reporting Bias</rdfs:label>
</owl:Class>
<owl:Axiom>
<owl:annotatedSource rdf:resource="https://w3id.org/aio/AnnotatorReportingBias"/>
<owl:annotatedProperty rdf:resource="http://purl.obolibrary.org/obo/IAO_0000115"/>
<owl:annotatedTarget>An individual bias occurring when users rely on automation as a heuristic replacement for their own information seeking and processing.</owl:annotatedTarget>
<oboInOwl:hasDbXref rdf:resource="https://doi.org/10.6028/NIST.SP.1270"/>
</owl:Axiom>
<!-- https://w3id.org/aio/ArtificialNeuralNetwork -->
<owl:Class rdf:about="https://w3id.org/aio/ArtificialNeuralNetwork">
<rdfs:subClassOf rdf:resource="https://w3id.org/aio/Network"/>
<obo:IAO_0000115>A network based on a collection of connected units called artificial neurons modeled after biological neurons.</obo:IAO_0000115>
<oboInOwl:hasExactSynonym>ANN</oboInOwl:hasExactSynonym>
<oboInOwl:hasExactSynonym>NN</oboInOwl:hasExactSynonym>
<oboInOwl:inSubset rdf:resource="https://w3id.org/aio/NetworkSubset"/>
<rdfs:comment>An artificial neural network (ANN) is based on a collection of connected units or nodes called artificial neurons, modeled after biological neurons, with connections transmitting signals processed by non-linear functions.</rdfs:comment>
<rdfs:label>Artificial Neural Network</rdfs:label>
</owl:Class>
<owl:Axiom>
<owl:annotatedSource rdf:resource="https://w3id.org/aio/ArtificialNeuralNetwork"/>
<owl:annotatedProperty rdf:resource="http://purl.obolibrary.org/obo/IAO_0000115"/>
<owl:annotatedTarget>A network based on a collection of connected units called artificial neurons modeled after biological neurons.</owl:annotatedTarget>
<oboInOwl:hasDbXref rdf:resource="https://en.wikipedia.org/wiki/Artificial_neural_network"/>
</owl:Axiom>
<!-- https://w3id.org/aio/AssociationRuleLearning -->
<owl:Class rdf:about="https://w3id.org/aio/AssociationRuleLearning">
<rdfs:subClassOf rdf:resource="https://w3id.org/aio/SupervisedLearning"/>
<obo:IAO_0000115>A supervised learning focused on a rule-based approach for discovering interesting relations between variables in large databases.</obo:IAO_0000115>
<oboInOwl:inSubset rdf:resource="https://w3id.org/aio/MachineLearningSubset"/>
<rdfs:label>Association Rule Learning</rdfs:label>
</owl:Class>
<owl:Axiom>
<owl:annotatedSource rdf:resource="https://w3id.org/aio/AssociationRuleLearning"/>
<owl:annotatedProperty rdf:resource="http://purl.obolibrary.org/obo/IAO_0000115"/>
<owl:annotatedTarget>A supervised learning focused on a rule-based approach for discovering interesting relations between variables in large databases.</owl:annotatedTarget>
<oboInOwl:hasDbXref rdf:resource="https://en.wikipedia.org/wiki/Association_rule_learning"/>
</owl:Axiom>
<!-- https://w3id.org/aio/AttentionLayer -->
<owl:Class rdf:about="https://w3id.org/aio/AttentionLayer">
<rdfs:subClassOf rdf:resource="https://w3id.org/aio/Layer"/>
<obo:IAO_0000115>A layer that implements dot-product attention also known as Luong-style attention.</obo:IAO_0000115>
<oboInOwl:inSubset rdf:resource="https://w3id.org/aio/LayerSubset"/>
<rdfs:comment>Dot-product attention layer, a.k.a. Luong-style attention.</rdfs:comment>
<rdfs:label>Attention Layer</rdfs:label>
</owl:Class>
<owl:Axiom>
<owl:annotatedSource rdf:resource="https://w3id.org/aio/AttentionLayer"/>
<owl:annotatedProperty rdf:resource="http://purl.obolibrary.org/obo/IAO_0000115"/>
<owl:annotatedTarget>A layer that implements dot-product attention also known as Luong-style attention.</owl:annotatedTarget>
<oboInOwl:hasDbXref rdf:resource="https://www.tensorflow.org/api_docs/python/tf/keras/layers/Attention"/>
</owl:Axiom>
<!-- https://w3id.org/aio/AutoEncoderNetwork -->
<owl:Class rdf:about="https://w3id.org/aio/AutoEncoderNetwork">
<rdfs:subClassOf rdf:resource="https://w3id.org/aio/UnsupervisedPretrainedNetwork"/>
<rdfs:subClassOf>
<owl:Restriction>
<owl:onProperty rdf:resource="http://purl.obolibrary.org/obo/BFO_0000051"/>
<owl:someValuesFrom rdf:resource="https://w3id.org/aio/HiddenLayer"/>
</owl:Restriction>
</rdfs:subClassOf>
<rdfs:subClassOf>
<owl:Restriction>
<owl:onProperty rdf:resource="http://purl.obolibrary.org/obo/BFO_0000051"/>
<owl:someValuesFrom rdf:resource="https://w3id.org/aio/MatchedInputOutputLayer"/>
</owl:Restriction>
</rdfs:subClassOf>
<obo:IAO_0000115>An unsupervised pretrained network that learns efficient codings of unlabeled data by training to ignore insignificant data and regenerate input from encoding.</obo:IAO_0000115>
<oboInOwl:hasExactSynonym>AE</oboInOwl:hasExactSynonym>
<oboInOwl:inSubset rdf:resource="https://w3id.org/aio/NetworkSubset"/>
<rdfs:comment>Layers: Input, Hidden, Matched Output-Input</rdfs:comment>
<rdfs:label>Auto Encoder Network</rdfs:label>
</owl:Class>
<owl:Axiom>
<owl:annotatedSource rdf:resource="https://w3id.org/aio/AutoEncoderNetwork"/>
<owl:annotatedProperty rdf:resource="http://purl.obolibrary.org/obo/IAO_0000115"/>
<owl:annotatedTarget>An unsupervised pretrained network that learns efficient codings of unlabeled data by training to ignore insignificant data and regenerate input from encoding.</owl:annotatedTarget>
<oboInOwl:hasDbXref rdf:resource="https://en.wikipedia.org/wiki/Autoencoder"/>
</owl:Axiom>
<!-- https://w3id.org/aio/AutomationComplacencyBias -->
<owl:Class rdf:about="https://w3id.org/aio/AutomationComplacencyBias">
<rdfs:subClassOf rdf:resource="https://w3id.org/aio/IndividualBias"/>
<obo:IAO_0000115>An individual bias characterized by over-reliance on automated systems leading to attenuated human skills.</obo:IAO_0000115>
<oboInOwl:hasExactSynonym>Automation Complaceny</oboInOwl:hasExactSynonym>
<oboInOwl:inSubset rdf:resource="https://w3id.org/aio/BiasSubset"/>
<rdfs:comment>Over-reliance on automated systems, leading to attenuated human skills, such as with spelling and autocorrect.</rdfs:comment>
<rdfs:label>Automation Complacency Bias</rdfs:label>
</owl:Class>
<owl:Axiom>
<owl:annotatedSource rdf:resource="https://w3id.org/aio/AutomationComplacencyBias"/>
<owl:annotatedProperty rdf:resource="http://purl.obolibrary.org/obo/IAO_0000115"/>
<owl:annotatedTarget>An individual bias characterized by over-reliance on automated systems leading to attenuated human skills.</owl:annotatedTarget>
<oboInOwl:hasDbXref rdf:resource="https://doi.org/10.6028/NIST.SP.1270"/>
</owl:Axiom>
<!-- https://w3id.org/aio/AutoregressiveConditionalHeteroskedasticity -->
<owl:Class rdf:about="https://w3id.org/aio/AutoregressiveConditionalHeteroskedasticity">
<rdfs:subClassOf rdf:resource="https://w3id.org/aio/Model"/>
<obo:IAO_0000115>A model that describes the variance of the current error term as a function of the previous periods' error terms, capturing volatility clustering. Used for time series data.</obo:IAO_0000115>
<oboInOwl:hasExactSynonym>ARCH</oboInOwl:hasExactSynonym>
<oboInOwl:inSubset rdf:resource="https://w3id.org/aio/ModelSubset"/>
<rdfs:label>Autoregressive Conditional Heteroskedasticity</rdfs:label>
</owl:Class>
<!-- https://w3id.org/aio/AutoregressiveDistributedLag -->
<owl:Class rdf:about="https://w3id.org/aio/AutoregressiveDistributedLag">
<rdfs:subClassOf rdf:resource="https://w3id.org/aio/Model"/>
<obo:IAO_0000115>A model that includes lagged values of both the dependent variable and one or more independent variables, capturing dynamic relationships over time. Used in time series analysis.</obo:IAO_0000115>
<oboInOwl:hasExactSynonym>ARDL</oboInOwl:hasExactSynonym>
<oboInOwl:inSubset rdf:resource="https://w3id.org/aio/ModelSubset"/>
<rdfs:label>Autoregressive Distributed Lag</rdfs:label>
</owl:Class>
<!-- https://w3id.org/aio/AutoregressiveIntegratedMovingAverage -->
<owl:Class rdf:about="https://w3id.org/aio/AutoregressiveIntegratedMovingAverage">
<rdfs:subClassOf rdf:resource="https://w3id.org/aio/Model"/>
<obo:IAO_0000115>A model which combines autoregression (AR), differencing (I), and moving average (MA) components. Used for analyzing and forecasting time series data.</obo:IAO_0000115>
<oboInOwl:hasExactSynonym>ARIMA</oboInOwl:hasExactSynonym>
<oboInOwl:inSubset rdf:resource="https://w3id.org/aio/ModelSubset"/>
<rdfs:label>Autoregressive Integrated Moving Average</rdfs:label>
</owl:Class>
<!-- https://w3id.org/aio/AutoregressiveLanguageModel -->
<owl:Class rdf:about="https://w3id.org/aio/AutoregressiveLanguageModel">
<rdfs:subClassOf rdf:resource="https://w3id.org/aio/LanguageModel"/>
<obo:IAO_0000115>A language model that generates text sequentially predicting one token at a time based on the previously generated tokens excelling at natural language generation tasks by modeling the probability distribution over sequences of tokens.</obo:IAO_0000115>
<oboInOwl:hasRelatedSynonym>generative language model</oboInOwl:hasRelatedSynonym>
<oboInOwl:hasRelatedSynonym>sequence-to-sequence model</oboInOwl:hasRelatedSynonym>
<oboInOwl:inSubset rdf:resource="https://w3id.org/aio/ModelSubset"/>
<rdfs:label>Autoregressive Language Model</rdfs:label>
</owl:Class>
<!-- https://w3id.org/aio/AutoregressiveMovingAverage -->
<owl:Class rdf:about="https://w3id.org/aio/AutoregressiveMovingAverage">
<rdfs:subClassOf rdf:resource="https://w3id.org/aio/Model"/>
<obo:IAO_0000115>A model that combines autoregressive (AR) and moving average (MA) components to represent time series data, suitable for stationary series without the need for differencing.</obo:IAO_0000115>
<oboInOwl:hasExactSynonym>ARMA</oboInOwl:hasExactSynonym>
<oboInOwl:inSubset rdf:resource="https://w3id.org/aio/ModelSubset"/>
<rdfs:label>Autoregressive Moving Average</rdfs:label>
</owl:Class>
<!-- https://w3id.org/aio/AvailabilityHeuristicBias -->
<owl:Class rdf:about="https://w3id.org/aio/AvailabilityHeuristicBias">
<rdfs:subClassOf rdf:resource="https://w3id.org/aio/IndividualBias"/>
<obo:IAO_0000115>An individual bias characterized by a mental shortcut where easily recalled information is overweighted in judgment and decision-making.</obo:IAO_0000115>
<oboInOwl:hasExactSynonym>Availability Bias</oboInOwl:hasExactSynonym>
<oboInOwl:hasExactSynonym>Availability Heuristic</oboInOwl:hasExactSynonym>
<oboInOwl:inSubset rdf:resource="https://w3id.org/aio/BiasSubset"/>
<rdfs:label>Availability Heuristic Bias</rdfs:label>
</owl:Class>
<owl:Axiom>
<owl:annotatedSource rdf:resource="https://w3id.org/aio/AvailabilityHeuristicBias"/>
<owl:annotatedProperty rdf:resource="http://purl.obolibrary.org/obo/IAO_0000115"/>
<owl:annotatedTarget>An individual bias characterized by a mental shortcut where easily recalled information is overweighted in judgment and decision-making.</owl:annotatedTarget>
<oboInOwl:hasDbXref rdf:resource="https://doi.org/10.6028/NIST.SP.1270"/>
</owl:Axiom>
<!-- https://w3id.org/aio/AverageLayer -->
<owl:Class rdf:about="https://w3id.org/aio/AverageLayer">
<rdfs:subClassOf rdf:resource="https://w3id.org/aio/MergingLayer"/>
<obo:IAO_0000115>A merging layer that averages a list of inputs element-wise taking as input a list of tensors all of the same shape.</obo:IAO_0000115>
<oboInOwl:inSubset rdf:resource="https://w3id.org/aio/LayerSubset"/>
<rdfs:comment>Layer that averages a list of inputs element-wise. It takes as input a list of tensors, all of the same shape, and returns a single tensor (also of the same shape).</rdfs:comment>
<rdfs:label>Average Layer</rdfs:label>
</owl:Class>
<owl:Axiom>
<owl:annotatedSource rdf:resource="https://w3id.org/aio/AverageLayer"/>
<owl:annotatedProperty rdf:resource="http://purl.obolibrary.org/obo/IAO_0000115"/>
<owl:annotatedTarget>A merging layer that averages a list of inputs element-wise taking as input a list of tensors all of the same shape.</owl:annotatedTarget>
<oboInOwl:hasDbXref rdf:resource="https://www.tensorflow.org/api_docs/python/tf/keras/layers/Average"/>
</owl:Axiom>
<!-- https://w3id.org/aio/AveragePooling1DLayer -->
<owl:Class rdf:about="https://w3id.org/aio/AveragePooling1DLayer">
<rdfs:subClassOf rdf:resource="https://w3id.org/aio/PoolingLayer"/>
<obo:IAO_0000115>A pooling layer that performs average pooling for temporal data.</obo:IAO_0000115>
<oboInOwl:hasExactSynonym>AvgPool1D</oboInOwl:hasExactSynonym>
<oboInOwl:inSubset rdf:resource="https://w3id.org/aio/LayerSubset"/>
<rdfs:comment>Average pooling for temporal data. Downsamples the input representation by taking the average value over the window defined by pool_size. The window is shifted by strides. The resulting output when using "valid" padding option has a shape of: output_shape = (input_shape - pool_size + 1) / strides). The resulting output shape when using the "same" padding option is: output_shape = input_shape / strides.</rdfs:comment>
<rdfs:label>AveragePooling1D Layer</rdfs:label>
</owl:Class>
<owl:Axiom>
<owl:annotatedSource rdf:resource="https://w3id.org/aio/AveragePooling1DLayer"/>
<owl:annotatedProperty rdf:resource="http://purl.obolibrary.org/obo/IAO_0000115"/>
<owl:annotatedTarget>A pooling layer that performs average pooling for temporal data.</owl:annotatedTarget>
<oboInOwl:hasDbXref rdf:resource="https://www.tensorflow.org/api_docs/python/tf/keras/layers/AveragePooling1D"/>
</owl:Axiom>
<!-- https://w3id.org/aio/AveragePooling2DLayer -->
<owl:Class rdf:about="https://w3id.org/aio/AveragePooling2DLayer">
<rdfs:subClassOf rdf:resource="https://w3id.org/aio/PoolingLayer"/>
<obo:IAO_0000115>A pooling layer that performs average pooling for spatial data.</obo:IAO_0000115>
<oboInOwl:hasExactSynonym>AvgPool2D</oboInOwl:hasExactSynonym>
<oboInOwl:inSubset rdf:resource="https://w3id.org/aio/LayerSubset"/>
<rdfs:comment>Average pooling operation for spatial data. Downsamples the input along its spatial dimensions (height and width) by taking the average value over an input window (of size defined by pool_size) for each channel of the input. The window is shifted by strides along each dimension. The resulting output when using "valid" padding option has a shape (number of rows or columns) of: output_shape = math.floor((input_shape - pool_size) / strides) + 1 (when input_shape >= pool_size). The resulting output shape when using the "same" padding option is: output_shape = math.floor((input_shape - 1) / strides) + 1.</rdfs:comment>
<rdfs:label>AveragePooling2D Layer</rdfs:label>
</owl:Class>
<owl:Axiom>
<owl:annotatedSource rdf:resource="https://w3id.org/aio/AveragePooling2DLayer"/>
<owl:annotatedProperty rdf:resource="http://purl.obolibrary.org/obo/IAO_0000115"/>
<owl:annotatedTarget>A pooling layer that performs average pooling for spatial data.</owl:annotatedTarget>
<oboInOwl:hasDbXref rdf:resource="https://www.tensorflow.org/api_docs/python/tf/keras/layers/AveragePooling2D"/>
</owl:Axiom>
<!-- https://w3id.org/aio/AveragePooling3DLayer -->
<owl:Class rdf:about="https://w3id.org/aio/AveragePooling3DLayer">
<rdfs:subClassOf rdf:resource="https://w3id.org/aio/PoolingLayer"/>
<obo:IAO_0000115>A pooling layer that performs average pooling for 3D data (spatial or spatio-temporal).</obo:IAO_0000115>
<oboInOwl:hasExactSynonym>AvgPool3D</oboInOwl:hasExactSynonym>
<oboInOwl:inSubset rdf:resource="https://w3id.org/aio/LayerSubset"/>
<rdfs:comment>Average pooling operation for 3D data (spatial or spatio-temporal). Downsamples the input along its spatial dimensions (depth, height, and width) by taking the average value over an input window (of size defined by pool_size) for each channel of the input. The window is shifted by strides along each dimension.</rdfs:comment>
<rdfs:label>AveragePooling3D Layer</rdfs:label>
</owl:Class>
<owl:Axiom>
<owl:annotatedSource rdf:resource="https://w3id.org/aio/AveragePooling3DLayer"/>
<owl:annotatedProperty rdf:resource="http://purl.obolibrary.org/obo/IAO_0000115"/>
<owl:annotatedTarget>A pooling layer that performs average pooling for 3D data (spatial or spatio-temporal).</owl:annotatedTarget>
<oboInOwl:hasDbXref rdf:resource="https://www.tensorflow.org/api_docs/python/tf/keras/layers/AveragePooling3D"/>
</owl:Axiom>
<!-- https://w3id.org/aio/AvgPool1DLayer -->
<owl:Class rdf:about="https://w3id.org/aio/AvgPool1DLayer">
<rdfs:subClassOf rdf:resource="https://w3id.org/aio/PoolingLayer"/>
<obo:IAO_0000115>A pooling layer that applies a 1D average pooling over an input signal composed of several input planes.</obo:IAO_0000115>
<oboInOwl:hasExactSynonym>AvgPool1D</oboInOwl:hasExactSynonym>
<oboInOwl:inSubset rdf:resource="https://w3id.org/aio/LayerSubset"/>
<rdfs:label>AvgPool1D Layer</rdfs:label>
</owl:Class>
<owl:Axiom>
<owl:annotatedSource rdf:resource="https://w3id.org/aio/AvgPool1DLayer"/>
<owl:annotatedProperty rdf:resource="http://purl.obolibrary.org/obo/IAO_0000115"/>
<owl:annotatedTarget>A pooling layer that applies a 1D average pooling over an input signal composed of several input planes.</owl:annotatedTarget>
<oboInOwl:hasDbXref rdf:resource="https://pytorch.org/docs/stable/nn.html#pooling-layers"/>
</owl:Axiom>
<!-- https://w3id.org/aio/AvgPool2DLayer -->
<owl:Class rdf:about="https://w3id.org/aio/AvgPool2DLayer">
<rdfs:subClassOf rdf:resource="https://w3id.org/aio/PoolingLayer"/>
<obo:IAO_0000115>A pooling layer that applies a 2D average pooling over an input signal composed of several input planes.</obo:IAO_0000115>
<oboInOwl:hasExactSynonym>AvgPool2D</oboInOwl:hasExactSynonym>
<oboInOwl:inSubset rdf:resource="https://w3id.org/aio/LayerSubset"/>
<rdfs:label>AvgPool2D Layer</rdfs:label>
</owl:Class>
<owl:Axiom>
<owl:annotatedSource rdf:resource="https://w3id.org/aio/AvgPool2DLayer"/>
<owl:annotatedProperty rdf:resource="http://purl.obolibrary.org/obo/IAO_0000115"/>
<owl:annotatedTarget>A pooling layer that applies a 2D average pooling over an input signal composed of several input planes.</owl:annotatedTarget>
<oboInOwl:hasDbXref rdf:resource="https://pytorch.org/docs/stable/nn.html#pooling-layers"/>
</owl:Axiom>
<!-- https://w3id.org/aio/AvgPool3DLayer -->
<owl:Class rdf:about="https://w3id.org/aio/AvgPool3DLayer">
<rdfs:subClassOf rdf:resource="https://w3id.org/aio/PoolingLayer"/>
<obo:IAO_0000115>A pooling layer that applies a 3D average pooling over an input signal composed of several input planes.</obo:IAO_0000115>
<oboInOwl:hasExactSynonym>AvgPool3D</oboInOwl:hasExactSynonym>
<oboInOwl:inSubset rdf:resource="https://w3id.org/aio/LayerSubset"/>
<rdfs:label>AvgPool3D Layer</rdfs:label>
</owl:Class>
<owl:Axiom>
<owl:annotatedSource rdf:resource="https://w3id.org/aio/AvgPool3DLayer"/>
<owl:annotatedProperty rdf:resource="http://purl.obolibrary.org/obo/IAO_0000115"/>
<owl:annotatedTarget>A pooling layer that applies a 3D average pooling over an input signal composed of several input planes.</owl:annotatedTarget>
<oboInOwl:hasDbXref rdf:resource="https://pytorch.org/docs/stable/nn.html#pooling-layers"/>
</owl:Axiom>
<!-- https://w3id.org/aio/BackfedInputLayer -->
<owl:Class rdf:about="https://w3id.org/aio/BackfedInputLayer">
<rdfs:subClassOf rdf:resource="https://w3id.org/aio/InputLayer"/>
<obo:IAO_0000115>An input layer that receives values from another layer.</obo:IAO_0000115>
<oboInOwl:inSubset rdf:resource="https://w3id.org/aio/LayerSubset"/>
<rdfs:label>Backfed Input Layer</rdfs:label>
</owl:Class>
<!-- https://w3id.org/aio/BatchNorm1DLayer -->
<owl:Class rdf:about="https://w3id.org/aio/BatchNorm1DLayer">
<rdfs:subClassOf rdf:resource="https://w3id.org/aio/BatchNormalizationLayer"/>
<obo:IAO_0000115>A batch normalization layer that applies Batch Normalization over a 2D or 3D input.</obo:IAO_0000115>
<oboInOwl:hasExactSynonym>BatchNorm1D</oboInOwl:hasExactSynonym>
<oboInOwl:inSubset rdf:resource="https://w3id.org/aio/LayerSubset"/>
<rdfs:comment>Applies Batch Normalization over a 2D or 3D input as described in the paper Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift .</rdfs:comment>
<rdfs:label>BatchNorm1D Layer</rdfs:label>
</owl:Class>
<owl:Axiom>
<owl:annotatedSource rdf:resource="https://w3id.org/aio/BatchNorm1DLayer"/>
<owl:annotatedProperty rdf:resource="http://purl.obolibrary.org/obo/IAO_0000115"/>
<owl:annotatedTarget>A batch normalization layer that applies Batch Normalization over a 2D or 3D input.</owl:annotatedTarget>
<oboInOwl:hasDbXref rdf:resource="https://pytorch.org/docs/stable/nn.html#normalization-layers"/>
</owl:Axiom>
<!-- https://w3id.org/aio/BatchNorm2DLayer -->
<owl:Class rdf:about="https://w3id.org/aio/BatchNorm2DLayer">
<rdfs:subClassOf rdf:resource="https://w3id.org/aio/BatchNormalizationLayer"/>
<obo:IAO_0000115>A batch normalization layer that applies Batch Normalization over a 4D input.</obo:IAO_0000115>
<oboInOwl:hasExactSynonym>BatchNorm2D</oboInOwl:hasExactSynonym>
<oboInOwl:inSubset rdf:resource="https://w3id.org/aio/LayerSubset"/>
<rdfs:comment>Applies Batch Normalization over a 4D input (a mini-batch of 2D inputs with additional channel dimension) as described in the paper Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift .</rdfs:comment>
<rdfs:label>BatchNorm2D Layer</rdfs:label>
</owl:Class>
<owl:Axiom>
<owl:annotatedSource rdf:resource="https://w3id.org/aio/BatchNorm2DLayer"/>
<owl:annotatedProperty rdf:resource="http://purl.obolibrary.org/obo/IAO_0000115"/>
<owl:annotatedTarget>A batch normalization layer that applies Batch Normalization over a 4D input.</owl:annotatedTarget>
<oboInOwl:hasDbXref rdf:resource="https://pytorch.org/docs/stable/nn.html#normalization-layers"/>
</owl:Axiom>
<!-- https://w3id.org/aio/BatchNorm3DLayer -->
<owl:Class rdf:about="https://w3id.org/aio/BatchNorm3DLayer">
<rdfs:subClassOf rdf:resource="https://w3id.org/aio/BatchNormalizationLayer"/>
<obo:IAO_0000115>A batch normalization layer that applies Batch Normalization over a 5D input.</obo:IAO_0000115>
<oboInOwl:hasExactSynonym>BatchNorm3D</oboInOwl:hasExactSynonym>
<oboInOwl:inSubset rdf:resource="https://w3id.org/aio/LayerSubset"/>
<rdfs:comment>Applies Batch Normalization over a 5D input (a mini-batch of 3D inputs with additional channel dimension) as described in the paper Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift .</rdfs:comment>
<rdfs:label>BatchNorm3D Layer</rdfs:label>
</owl:Class>
<owl:Axiom>
<owl:annotatedSource rdf:resource="https://w3id.org/aio/BatchNorm3DLayer"/>
<owl:annotatedProperty rdf:resource="http://purl.obolibrary.org/obo/IAO_0000115"/>
<owl:annotatedTarget>A batch normalization layer that applies Batch Normalization over a 5D input.</owl:annotatedTarget>
<oboInOwl:hasDbXref rdf:resource="https://pytorch.org/docs/stable/nn.html#normalization-layers"/>
</owl:Axiom>
<!-- https://w3id.org/aio/BatchNormalizationLayer -->
<owl:Class rdf:about="https://w3id.org/aio/BatchNormalizationLayer">
<rdfs:subClassOf rdf:resource="https://w3id.org/aio/NormalizationLayer"/>
<obo:IAO_0000115>A normalization layer that normalizes its inputs applying a transformation that maintains the mean close to 0 and the standard deviation close to 1.</obo:IAO_0000115>
<oboInOwl:hasExactSynonym>BatchNorm</oboInOwl:hasExactSynonym>
<oboInOwl:inSubset rdf:resource="https://w3id.org/aio/LayerSubset"/>
<rdfs:comment>Layer that normalizes its inputs. Batch normalization applies a transformation that maintains the mean output close to 0 and the output standard deviation close to 1. Importantly, batch normalization works differently during training and during inference. During training (i.e. when using fit() or when calling the layer/model with the argument training=True), the layer normalizes its output using the mean and standard deviation of the current batch of inputs. That is to say, for each channel being normalized, the layer returns gamma * (batch - mean(batch)) / sqrt(var(batch) + epsilon) + beta, where: epsilon is small constant (configurable as part of the constructor arguments), gamma is a learned scaling factor (initialized as 1), which can be disabled by passing scale=False to the constructor. beta is a learned offset factor (initialized as 0), which can be disabled by passing center=False to the constructor. During inference (i.e. when using evaluate() or predict() or when calling the layer/model with the argument training=False (which is the default), the layer normalizes its output using a moving average of the mean and standard deviation of the batches it has seen during training. That is to say, it returns gamma * (batch - self.moving_mean) / sqrt(self.moving_var + epsilon) + beta. self.moving_mean and self.moving_var are non-trainable variables that are updated each time the layer in called in training mode, as such: moving_mean = moving_mean * momentum + mean(batch) * (1 - momentum) moving_var = moving_var * momentum + var(batch) * (1 - momentum).</rdfs:comment>
<rdfs:label>BatchNormalization Layer</rdfs:label>
</owl:Class>
<owl:Axiom>
<owl:annotatedSource rdf:resource="https://w3id.org/aio/BatchNormalizationLayer"/>
<owl:annotatedProperty rdf:resource="http://purl.obolibrary.org/obo/IAO_0000115"/>
<owl:annotatedTarget>A normalization layer that normalizes its inputs applying a transformation that maintains the mean close to 0 and the standard deviation close to 1.</owl:annotatedTarget>
<oboInOwl:hasDbXref rdf:resource="https://www.tensorflow.org/api_docs/python/tf/keras/layers/BatchNormalization"/>
</owl:Axiom>
<!-- https://w3id.org/aio/BayesianNetwork -->
<owl:Class rdf:about="https://w3id.org/aio/BayesianNetwork">
<rdfs:subClassOf rdf:resource="https://w3id.org/aio/Network"/>
<obo:IAO_0000115>A network that is a probabilistic graphical model representing variables and their conditional dependencies via a directed acyclic graph.</obo:IAO_0000115>
<oboInOwl:inSubset rdf:resource="https://w3id.org/aio/NetworkSubset"/>
<rdfs:label>Bayesian Network</rdfs:label>
</owl:Class>
<owl:Axiom>
<owl:annotatedSource rdf:resource="https://w3id.org/aio/BayesianNetwork"/>
<owl:annotatedProperty rdf:resource="http://purl.obolibrary.org/obo/IAO_0000115"/>
<owl:annotatedTarget>A network that is a probabilistic graphical model representing variables and their conditional dependencies via a directed acyclic graph.</owl:annotatedTarget>
<oboInOwl:hasDbXref rdf:resource="https://en.wikipedia.org/wiki/Bayesian_network"/>
</owl:Axiom>
<!-- https://w3id.org/aio/BehavioralBias -->
<owl:Class rdf:about="https://w3id.org/aio/BehavioralBias">
<rdfs:subClassOf rdf:resource="https://w3id.org/aio/IndividualBias"/>
<obo:IAO_0000115>An individual bias characterized by systematic distortions in user behavior across platforms or contexts or across users represented in different datasets.</obo:IAO_0000115>
<oboInOwl:inSubset rdf:resource="https://w3id.org/aio/BiasSubset"/>
<rdfs:comment>Systematic distortions in user behavior across platforms or contexts, or across users represented in different datasets.</rdfs:comment>
<rdfs:label>Behavioral Bias</rdfs:label>
</owl:Class>
<owl:Axiom>
<owl:annotatedSource rdf:resource="https://w3id.org/aio/BehavioralBias"/>
<owl:annotatedProperty rdf:resource="http://purl.obolibrary.org/obo/IAO_0000115"/>
<owl:annotatedTarget>An individual bias characterized by systematic distortions in user behavior across platforms or contexts or across users represented in different datasets.</owl:annotatedTarget>
<oboInOwl:hasDbXref rdf:resource="https://doi.org/10.6028/NIST.SP.1270"/>
</owl:Axiom>
<!-- https://w3id.org/aio/Bias -->
<owl:Class rdf:about="https://w3id.org/aio/Bias">
<rdfs:subClassOf rdf:resource="http://www.w3.org/2002/07/owl#Thing"/>
<obo:IAO_0000115>A systematic error introduced into sampling or testing by selecting or encouraging one outcome or answer over others.</obo:IAO_0000115>
<oboInOwl:inSubset rdf:resource="https://w3id.org/aio/BiasSubset"/>
<rdfs:label>Bias</rdfs:label>
</owl:Class>
<owl:Axiom>
<owl:annotatedSource rdf:resource="https://w3id.org/aio/Bias"/>
<owl:annotatedProperty rdf:resource="http://purl.obolibrary.org/obo/IAO_0000115"/>
<owl:annotatedTarget>A systematic error introduced into sampling or testing by selecting or encouraging one outcome or answer over others.</owl:annotatedTarget>
<oboInOwl:hasDbXref rdf:resource="https://www.merriam-webster.com/dictionary/bias"/>
</owl:Axiom>
<!-- https://w3id.org/aio/Biclustering -->
<owl:Class rdf:about="https://w3id.org/aio/Biclustering">
<rdfs:subClassOf rdf:resource="https://w3id.org/aio/MachineLearningTask"/>
<obo:IAO_0000115>A machine learning task focused on methods that simultaneously cluster the rows and columns of a matrix to identify submatrices with coherent patterns.</obo:IAO_0000115>
<oboInOwl:hasExactSynonym>Block Clustering</oboInOwl:hasExactSynonym>
<oboInOwl:hasExactSynonym>Co-clustering</oboInOwl:hasExactSynonym>
<oboInOwl:hasExactSynonym>Joint Clustering</oboInOwl:hasExactSynonym>
<oboInOwl:hasExactSynonym>Two-mode Clustering</oboInOwl:hasExactSynonym>
<oboInOwl:hasExactSynonym>Two-way Clustering</oboInOwl:hasExactSynonym>
<oboInOwl:inSubset rdf:resource="https://w3id.org/aio/MachineLearningSubset"/>
<rdfs:label>Biclustering</rdfs:label>
</owl:Class>
<owl:Axiom>
<owl:annotatedSource rdf:resource="https://w3id.org/aio/Biclustering"/>
<owl:annotatedProperty rdf:resource="http://purl.obolibrary.org/obo/IAO_0000115"/>
<owl:annotatedTarget>A machine learning task focused on methods that simultaneously cluster the rows and columns of a matrix to identify submatrices with coherent patterns.</owl:annotatedTarget>
<oboInOwl:hasDbXref rdf:resource="https://en.wikipedia.org/wiki/Biclustering"/>
</owl:Axiom>