PyTorch version of Stable Baselines, reliable implementations of reinforcement learning algorithms.
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Updated
Feb 21, 2026 - Python
PyTorch version of Stable Baselines, reliable implementations of reinforcement learning algorithms.
Lightning fast forecasting with statistical and econometric models.
A fork of OpenAI Baselines, implementations of reinforcement learning algorithms
Scalable and user friendly neural forecasting algorithms.
An index of algorithms for learning causality with data
Shou Lu NLPJing Sai Ce Lue Shi Xian , Ge Ren Wu baseline, Xiang Guan Jing Sai Jing Yan Tie (Dang Qian Sai Shi , Wang Qi Sai Shi , Xun Lian Sai ), NLPHui Yi Shi Jian , Chang Yong Zi Mei Ti , GPUTui Jian Deng ,Chi Xu Geng Xin Zhong
Probabilistic Hierarchical forecasting with statistical and econometric methods.
S-RL Toolbox: Reinforcement Learning (RL) and State Representation Learning (SRL) for Robotics
RLeXplore provides stable baselines of exploration methods in reinforcement learning, such as intrinsic curiosity module (ICM), random network distillation (RND) and rewarding impact-driven exploration (RIDE).
Continual learning baselines and strategies from popular papers, using Avalanche. We include EWC, SI, GEM, AGEM, LwF, iCarl, GDumb, and other strategies.
Mirror of Stable-Baselines: a fork of OpenAI Baselines, implementations of reinforcement learning algorithms
Multi-turn dialogue baselines written in PyTorch
Re-implementations of SOTA RL algorithms.
Baseline classifiers on the polluted MNIST dataset, SJTU CS420 course project
A well-documented A2C written in PyTorch
Some common recommendation system baseline, with description and link.
Implementations of Multi-Task and Meta-Learning baselines for the Metaworld benchmark
An OpenAI Gym and Reinforcement Learning Library built in Typescript
This work considers combine multi-tricks with highway network to achieve traffic flow prediction accurately.
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