One of the most important objectives of the Continual AI project is to provide easy access to Continual Learning both in terms of didactic materials and open software/datasets for business/research. In this page we will try to collect every open-source project related to Continual Learning.
Sequoia Library: A Playground for research at the intersection of Continual, Reinforcement, and Self-Supervised Learning.
Continuum: Continuum is a Python library (written with PyTorch) for loading of datasets in Continual Learning. It supports many datasets and most CL scenarios (NC, NI, NIC…).
NORB sequencer: Java application (with GUI) to make small videos out of the NORB dataset.
GEM implementation: Implementation of the CL strategy “Gradient Episodic Memory”.
OpenAI Gym: Open source interface that provides a ready-to-use suite of reinforcement learning tasks for evaluating performance of your algorithm.
DeepMind Lab: 3D learning environment that provides a suite of challenging 3D navigation and puzzle-solving tasks for learning agents.
DEN: TensorFlow implementation of the CL strategy “Dynamically Expandable Networks”.
CORe50 benchmark: Continual Learning benchmark for object recognition and robotics.
OpenLORIS-Object: A Dataset and Benchmark towards Lifelong Object Recognition
Stream-51: Streaming Classification and Novelty Detection from Videos
CRIB: Synthetic, incremental object learning environment that can produce data that models visual imagery produced by object exploration in early infancy
Visual Domain Decathlon: Ten image classification problems representative of very different visual domains.
iCubWord Transformation: a Dataset for Continual Learning and Robotics.
Omniglot: A dataset for few shot, meta-learning and continual learning.
NICO: Towards Non-i.i.d. Image Classification.