🌊 Online machine learning in Python
-
Updated
Nov 23, 2024 - Python
🌊 Online machine learning in Python
PyTorch implementation of various methods for continual learning (XdG, EWC, SI, LwF, FROMP, DGR, BI-R, ER, A-GEM, iCaRL, Generative Classifier) in three different scenarios.
Train, Evaluate, Optimize, Deploy Computer Vision Models via OpenVINO™
(CVPR 2021 Oral) Open World Object Detection
PyCIL: A Python Toolbox for Class-Incremental Learning
An Incremental Learning, Continual Learning, and Life-Long Learning Repository
Framework for Analysis of Class-Incremental Learning with 12 state-of-the-art methods and 3 baselines.
Evaluate three types of task shifting with popular continual learning algorithms.
A clean and simple data loading library for Continual Learning
A collection of incremental learning paper implementations including PODNet (ECCV20) and Ghost (CVPR-W21).
A collection of online continual learning paper implementations and tricks for computer vision in PyTorch, including our ASER(AAAI-21), SCR(CVPR21-W) and an online continual learning survey (Neurocomputing).
🎉 PILOT: A Pre-trained Model-Based Continual Learning Toolbox
The efficient SMT-based context-bounded model checker (ESBMC)
Streaming Anomaly Detection Framework in Python (Outlier Detection for Streaming Data)
A brain-inspired version of generative replay for continual learning with deep neural networks (e.g., class-incremental learning on CIFAR-100; PyTorch code).
Continual Hyperparameter Selection Framework. Compares 11 state-of-the-art Lifelong Learning methods and 4 baselines. Official Codebase of "A continual learning survey: Defying forgetting in classification tasks." in IEEE TPAMI.
PyTorch Implementation of Learning to Prompt (L2P) for Continual Learning @ CVPR22
Fwumious Wabbit, fast on-line machine learning toolkit written in Rust
Elastic weight consolidation technique for incremental learning.
The Tornado 🌪️ framework, designed and implemented for adaptive online learning and data stream mining in Python.
Add a description, image, and links to the incremental-learning topic page so that developers can more easily learn about it.
To associate your repository with the incremental-learning topic, visit your repo's landing page and select "manage topics."