PyTorch version of Stable Baselines, reliable implementations of reinforcement learning algorithms.

A fork of OpenAI Baselines, implementations of reinforcement learning algorithms

Lightning ⚡️ fast forecasting with statistical and econometric models.

Scalable and user friendly neural 🧠 forecasting algorithms.

An index of algorithms for learning causality with data

收录NLP竞赛策略实现、各任务baseline、相关竞赛经验贴（当前赛事、往期赛事、训练赛）、NLP会议时间、常用自媒体、GPU推荐等，持续更新中

S-RL Toolbox: Reinforcement Learning (RL) and State Representation Learning (SRL) for Robotics

Probabilistic Hierarchical forecasting 👑 with statistical and econometric methods.

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).

Mirror of Stable-Baselines: a fork of OpenAI Baselines, implementations of reinforcement learning algorithms

Continual learning baselines and strategies from popular papers, using Avalanche. We include EWC, SI, GEM, AGEM, LwF, iCarl, GDumb, and other strategies.

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.

Deep Developmental Reinforcement Learning

京东JDD猪脸识别比赛

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.