Popular GitHub Repositories for Soft Discrepancy

Softlearning is a reinforcement learning framework for training maximum entropy policies in continuous domains. Includes the official implementation of the Soft Actor-Critic algorithm.

PyTorch implementation of Soft Actor-Critic (SAC), Twin Delayed DDPG (TD3), Actor-Critic (AC/A2C), Proximal Policy Optimization (PPO), QT-Opt, PointNet..

32 projects in the framework of Deep Reinforcement Learning algorithms: Q-learning, DQN, PPO, DDPG, TD3, SAC, A2C and others. Each project is provided with a detailed training log.

About Code release for "Anomaly Transformer: Time Series Anomaly Detection with Association Discrepancy" (ICLR 2022 Spotlight), https://openreview.net/forum?id=LzQQ89U1qm_

PyTorch implementation of soft actor critic

JAX (Flax) implementation of algorithms for Deep Reinforcement Learning with continuous action spaces.

A PyTorch library for building deep reinforcement learning agents.

Reinforcement Learning for real-time applications - host of the TrackMania Roborace League

[IJCAI18] SSR-Net: A Compact Soft Stagewise Regression Network for Age Estimation

PyTorch implementation of Soft Actor-Critic (SAC)

Soft speech units for voice conversion

DrQ: Data regularized Q

RAD: Reinforcement Learning with Augmented Data

lagom: A PyTorch infrastructure for rapid prototyping of reinforcement learning algorithms.

HuBERT content encoders for: A Comparison of Discrete and Soft Speech Units for Improved Voice Conversion

Your ? Superintelligence

Ytk-learn is a distributed machine learning library which implements most of popular machine learning algorithms(GBDT, GBRT, Mixture Logistic Regression, Gradient Boosting Soft Tree, Factorization Machines, Field-aware Factorization Machines, Logistic Regression, Softmax).

Action recognition using soft attention based deep recurrent neural networks

DeepRL algorithms implementation easy for understanding and reading with Pytorch and Tensorflow 2(DQN, REINFORCE, VPG, A2C, TRPO, PPO, DDPG, TD3, SAC)

Implementation of Soft MoE, proposed by Brain's Vision team, in Pytorch