🌊 Online machine learning in Python
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Updated
Mar 6, 2025 - Python
🌊 Online machine learning in Python
Train, Evaluate, Optimize, Deploy Computer Vision Models via OpenVINO™
(CVPR 2021 Oral) Open World Object Detection
PyCIL: A Python Toolbox for Class-Incremental Learning
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
🎉 PILOT: A Pre-trained Model-Based Continual Learning Toolbox
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 survey (Neurocomputing).
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
This repository collects awesome survey, resource, and paper for lifelong learning LLM agents
Revisiting Class-Incremental Learning with Pre-Trained Models: Generalizability and Adaptivity are All You Need (IJCV 2024)
The Tornado 🌪️ framework, designed and implemented for adaptive online learning and data stream mining in Python.
(TPAMI 2021) iOD: Incremental Object Detection via Meta-Learning
Online anomaly detection for data streams/ Real-time anomaly detection for time series data.
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