an R package for structural equation modeling and more
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Updated
Nov 26, 2024 - R
an R package for structural equation modeling and more
🎓 Tidy tools for academics
An R package for Bayesian structural equation modeling
Causing: CAUsal INterpretation using Graphs
REGAIN (Regularised Graphical Inference)
An Introduction to Structural Equation Modeling
Data Analysis on Mental Health.
This is the source code for HDNO: a hierarchical model for task-oriented dialogue system.
AI that generates human faces which have never been seen before. The future is now 😁
PyTorch implementation of "Variational Autoencoders with Jointly Optimized Latent Dependency Structure" [ICLR 2019]
Ωnyx - Structural Equation Modeling
Tensor Extraction of Latent Features (T-ELF). Within T-ELF's arsenal are non-negative matrix and tensor factorization solutions, equipped with automatic model determination (also known as the estimation of latent factors - rank) for accurate data modeling. Our software suite encompasses cutting-edge data pre-processing and post-processing modules.
An R package for the Latent Environmental & Genetic InTeraction (LEGIT) model
High-Performance Implementation of Spectral Learning of Latent-Variable PCFGs (Cohen et al., 2013)
Match Predictions for Professional League of Legends Matches
Jumping across biomedical contexts using compressive data fusion
A Mutually-Dependent Hadamard Kernel for Modelling Latent Variable Couplings (ACML 2017)
[Pytorch] Minimal implementation of a Variational Autoencoder (VAE) with Categorical Latent variables inspired from "Categorical Reparameterization with Gumbel-Softmax".
Coordinate ascent mean-field variational inference (CAVI) using the evidence lower bound (ELBO) to iteratively perform the optimal variational factor distribution parameter updates for clustering.
R package for penalized factor analysis via trust-region algorithm and automatic multiple tuning parameter selection
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