Popular GitHub Repositories for Soft Threshold Reparameterization

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.

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

Action recognition using soft attention based deep recurrent neural networks

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).

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

[NeurIPS 2021 Spotlight] & [IJCV 2024] SOFT: Softmax-free Transformer with Linear Complexity

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