Author's PyTorch implementation of TD3+BC, a simple variant of TD3 for offline RL

Last update: Dec 23, 2022

Related tags

Overview

A Minimalist Approach to Offline Reinforcement Learning

TD3+BC is a simple approach to offline RL where only two changes are made to TD3: (1) a weighted behavior cloning loss is added to the policy update and (2) the states are normalized. Unlike competing methods there are no changes to architecture or underlying hyperparameters.

Usage

Paper results were collected with MuJoCo 1.50 (and mujoco-py 1.50.1.1) in OpenAI gym 0.17.0 with the D4RL datasets. Networks are trained using PyTorch 1.4.0 and Python 3.6.

The paper results can be reproduced by running:

./run_experiments.sh

Owner

Scott Fujimoto

GitHub Repository

Specificity-preserving RGB-D Saliency Detection

Specificity-preserving RGB-D Saliency Detection Authors: Tao Zhou, Huazhu Fu, Geng Chen, Yi Zhou, Deng-Ping Fan, and Ling Shao. 1. Preface This reposi

35 Jan 08, 2023

Self-supervised learning algorithms provide a way to train Deep Neural Networks in an unsupervised way using contrastive losses

Self-supervised learning Self-supervised learning algorithms provide a way to train Deep Neural Networks in an unsupervised way using contrastive loss

2 Mar 26, 2022

This is an (re-)implementation of DeepLab-ResNet in TensorFlow for semantic image segmentation on the PASCAL VOC dataset.

DeepLab-ResNet-TensorFlow This is an (re-)implementation of DeepLab-ResNet in TensorFlow for semantic image segmentation on the PASCAL VOC dataset. Up

19 Jan 16, 2022

Author's PyTorch implementation of TD3+BC, a simple variant of TD3 for offline RL

Related tags

Overview

A Minimalist Approach to Offline Reinforcement Learning

Usage

Owner

Scott Fujimoto

Specificity-preserving RGB-D Saliency Detection

Self-supervised learning algorithms provide a way to train Deep Neural Networks in an unsupervised way using contrastive losses

Unoffical implementation about Image Super-Resolution via Iterative Refinement by Pytorch

A python library for implementing a recommender system

Code for NeurIPS2021 submission "A Surrogate Objective Framework for Prediction+Programming with Soft Constraints"

a generic C++ library for image analysis

Domain Adaptation with Invariant RepresentationLearning: What Transformations to Learn?

Code To Tune or Not To Tune? Zero-shot Models for Legal Case Entailment.

Pytorch implementation of SELF-ATTENTIVE VAD, ICASSP 2021

Implementation of "The Power of Scale for Parameter-Efficient Prompt Tuning"

Python tools for 3D face: 3DMM, Mesh processing(transform, camera, light, render), 3D face representations.

Space Ship Simulator using python

A Broader Picture of Random-walk Based Graph Embedding

Feature board for ERPNext

3DV 2021: Synergy between 3DMM and 3D Landmarks for Accurate 3D Facial Geometry

GBK-GNN: Gated Bi-Kernel Graph Neural Networks for Modeling Both Homophily and Heterophily

Code for One-shot Talking Face Generation from Single-speaker Audio-Visual Correlation Learning (AAAI 2022)

Born-Infeld (BI) for AI: Energy-Conserving Descent (ECD) for Optimization

Pytorch code for "State-only Imitation with Transition Dynamics Mismatch" (ICLR 2020)

This is an (re-)implementation of DeepLab-ResNet in TensorFlow for semantic image segmentation on the PASCAL VOC dataset.