souradip-chakraborty Goto Github PK

gnn_rl

reinforcement learning with pytorch geometric library

google-research

Google Research

graphpolicynetworkactivelearning

The source code for NeurIPS 2020 paper "Graph Policy Network for Transferable Active Learning on Graphs"

guided-cost-learning

Implementation of the paper https://arxiv.org/abs/1603.00448.

gym_toy

Toy problems for OpenAI Gym

handful-of-trials-pytorch

Unofficial Pytorch code for "Deep Reinforcement Learning in a Handful of Trials using Probabilistic Dynamics Models"

har-recognition-

HARCNN: End-to-end Deep Learning-based Personalized Human Activity Recognition Framework

inverse-rl

Robot Learning from Expert Demonstration Using IRL

irl-maxent

Maximum Entropy and Maximum Causal Entropy Inverse Reinforcement Learning Implementation in Python

jekyll-now

Build a Jekyll blog in minutes, without touching the command line.

ksd-thinning

Online and informative thinning of MCMC samples using the Kernelized Stein Discrepancy (KSD)

ksrl

Posterior Coreset Construction with Kernelized Stein Discrepancy for Model-Based Reinforcement Learning

logo

Code for Reinforcement Learning with Sparse Rewards using Guidance from Offline Demonstration, ICLR 2022 (Spotlight)

mamba

This code accompanies the paper "Scalable Multi-Agent Model-Based Reinforcement Learning".

mbpg

PyTorch Implementation of Momentum-Based Policy Gradient Methods

mbpo_pytorch

A pytorch reprelication of the model-based reinforcement learning algorithm MBPO

mbpsrl

Code for paper: Model-based Reinforcement Learning for Continuous Control with Posterior Sampling (https://arxiv.org/abs/2012.09613)

mrn

ncpl

neural_testbed

oderl

Experiment code for "Continuous-Time Model-Based Reinforcement Learning"

optimistic-psrl-experiments

Respository for the paper "Optimistic Posterior Sampling for Reinforcement Learning with Few Samples and Tight Guarantees"

option-critic-pytorch

PyTorch implementation of the Option-Critic framework, Harb et al. 2016

pcmlp

pg_travel

Policy Gradient algorithms (REINFORCE, NPG, TRPO, PPO)

pilco-gpytorch

probability-and-generative-models

Basics about Generative modelling and Variational Inference

propagnada-detection

propaganda detection in news articles

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).

pytorch-rl

PyTorch implementation of Deep Reinforcement Learning: Policy Gradient methods (TRPO, PPO, A2C) and Generative Adversarial Imitation Learning (GAIL). Fast Fisher vector product TRPO.