tzs930

DRBC

dro

A package of distributionally robust optimization (DRO) methods. Implemented via cvxpy and PyTorch

MC-LAVE-RL

ICLR 2021: "Monte-Carlo Planning and Learning with Language Action Value Estimates"

Awesome-Realistic-Semi-Supervised-Learning

An awesome paper list of Semi-Supervised Learning under realistic settings.

palr

stable-baselines3-contrib

Contrib package for Stable-Baselines3 - Experimental reinforcement learning (RL) code

Resolving_copycat_problems_via_residual_prediction

This is an official code for paper Resolving Copycat Problems in Visual Imitation Learning via Residual Action Prediction https://arxiv.org/abs/2207.09705.

MVTCAE

imitation-dice

DSTC10-SIMMC

Repository (preliminary codes) for DSTC10 SIMMC track.

imitation-dice

AutomaticWatchFaces

optidice

OptiDICE: Offline Policy Optimization via Stationary Distribution Correction Estimation

mbrl-lib

Library for Model Based RL

CQL

Code for conservative Q-learning

JEM

Project site for "Your Classifier is Secretly an Energy-Based Model and You Should Treat it Like One"

repb-sde

IIAE

probprog20

stable-baselines-tf2

Explainable & Easy-to-debug Deep Reinforcement Learning Framework

pytorch-a2c-ppo-acktr-gail

PyTorch implementation of Advantage Actor Critic (A2C), Proximal Policy Optimization (PPO), Scalable trust-region method for deep reinforcement learning using Kronecker-factored approximation (ACKTR) and Generative Adversarial Imitation Learning (GAIL).

minirts

We release dataset collected for our research, code that implement neural network models described in the paper, and scripts to reproduce all of our results, and visualization tool for visualize dataset.

sac

Soft Actor-Critic

lime-experiments

Code for all experiments.

BGAIL

Bayesian Approach to Generative Adversarial Imitation Learning

tf-explain

Interpretability Methods for tf.keras models with Tensorflow 2.x

DNDT

Deep Neural Decision Trees

lime

Lime: Explaining the predictions of any machine learning classifier

RepBM

Representation Balancing MDPs for Off-Policy Policy Evaluation

softlearning

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