Repository for MDPGT

Last update: Dec 30, 2021

Related tags

Deep Learning MD-PGT

Overview

MD-PGT

Repository for implementing and reproducing the results for the paper MDPGT: Momentum-based Decentralized Policy Gradient Tracking.

Available Environments

Lineworld
Particle-world (installation instructions available at https://github.com/xylee95/MDPGT_particleworld)

Available Agents

DPG: Decentralized Policy Gradients
MDPG : Momentum Decentralized Policy Gradients
MDPGT : Momentum-based Decentralized Policy Gradient Tracking

Main files used are:

train_lineworld_dpg.py
train_lineworld_mdpg.py
train_lineworld_mdpgt.py
train_particleworld_dpg.py
train_particleworld_mdpg.py
train_particleworld_mdpgt.py
model.py : code for policy network and related functions
update_functions.py : all functions related to update rules and consensus for MDPG and MDPGT

Both MDPG and MDPGT has the option of using Minibatch Initialization to compute batch gradient surrogate.

Reproducing the results:

To reproduce the results shown in the paper, please check run_exp.sh for the relevant python commands.

Owner

Xian Yeow Lee

Graduate student at Iowa State University

Xian Yeow Lee

GitHub Repository

Self-Supervised Pre-Training for Transformer-Based Person Re-Identification

Self-Supervised Pre-Training for Transformer-Based Person Re-Identification [pdf] The official repository for Self-Supervised Pre-Training for Transfo

116 Jan 04, 2023

[CVPR 2020] Local Class-Specific and Global Image-Level Generative Adversarial Networks for Semantic-Guided Scene Generation

Contents Local and Global GAN Cross-View Image Translation Semantic Image Synthesis Acknowledgments Related Projects Citation Contributions Collaborat

131 Dec 07, 2022

Contains modeling practice materials and homework for the Computational Neuroscience course at Okinawa Institute of Science and Technology

A310 Computational Neuroscience - Okinawa Institute of Science and Technology, 2022 This repository contains modeling practice materials and homework

1 Jan 24, 2022

RL agent to play μRTS with Stable-Baselines3

Gym-μRTS with Stable-Baselines3/PyTorch This repo contains an attempt to reproduce Gridnet PPO with invalid action masking algorithm to play μRTS usin

24 Nov 11, 2022

Pytorch Implementation of Value Retrieval with Arbitrary Queries for Form-like Documents.

Value Retrieval with Arbitrary Queries for Form-like Documents Introduction Pytorch Implementation of Value Retrieval with Arbitrary Queries for Form-

13 Sep 15, 2022

Code for HLA-Face: Joint High-Low Adaptation for Low Light Face Detection (CVPR21)

HLA-Face: Joint High-Low Adaptation for Low Light Face Detection The official PyTorch implementation for HLA-Face: Joint High-Low Adaptation for Low L

77 Dec 08, 2022

When in Doubt: Improving Classification Performance with Alternating Normalization

When in Doubt: Improving Classification Performance with Alternating Normalization Findings of EMNLP 2021 Menglin Jia, Austin Reiter, Ser-Nam Lim, Yoa

13 Nov 06, 2022

source code and pre-trained/fine-tuned checkpoint for NAACL 2021 paper LightningDOT

LightningDOT: Pre-training Visual-Semantic Embeddings for Real-Time Image-Text Retrieval This repository contains source code and pre-trained/fine-tun

65 Dec 26, 2022

Interpretation of T cell states using reference single-cell atlases

Interpretation of T cell states using reference single-cell atlases ProjecTILs is a computational method to project scRNA-seq data into reference sing

139 Jan 03, 2023

Neural Dynamic Policies for End-to-End Sensorimotor Learning

This is a PyTorch based implementation for our NeurIPS 2020 paper on Neural Dynamic Policies for end-to-end sensorimotor learning.

47 Dec 11, 2022

Markov Attention Models

Introduction This repo contains code for reproducing the results in the paper Graphical Models with Attention for Context-Specific Independence and an

0 Dec 09, 2021

SkipGNN: Predicting Molecular Interactions with Skip-Graph Networks (Scientific Reports)

SkipGNN: Predicting Molecular Interactions with Skip-Graph Networks Molecular interaction networks are powerful resources for the discovery. While dee

49 Oct 15, 2022

Official PyTorch code of Holistic 3D Scene Understanding from a Single Image with Implicit Representation (CVPR 2021)

Implicit3DUnderstanding (Im3D) [Project Page] Holistic 3D Scene Understanding from a Single Image with Implicit Representation Cheng Zhang, Zhaopeng C

149 Jan 08, 2023

Fast, modular reference implementation of Instance Segmentation and Object Detection algorithms in PyTorch.

Faster R-CNN and Mask R-CNN in PyTorch 1.0 maskrcnn-benchmark has been deprecated. Please see detectron2, which includes implementations for all model

9k Jan 04, 2023

PyTorch code for our paper "Gated Multiple Feedback Network for Image Super-Resolution" (BMVC2019)

Gated Multiple Feedback Network for Image Super-Resolution This repository contains the PyTorch implementation for the proposed GMFN [arXiv]. The fram

66 Nov 03, 2022

Drone detection using YOLOv5

This drone detection system uses YOLOv5 which is a family of object detection architectures and we have trained the model on Drone Dataset. Overview I

27 Dec 20, 2022

An implementation demo of the ICLR 2021 paper Neural Attention Distillation: Erasing Backdoor Triggers from Deep Neural Networks in PyTorch.

Neural Attention Distillation This is an implementation demo of the ICLR 2021 paper Neural Attention Distillation: Erasing Backdoor Triggers from Deep

84 Jan 04, 2023

code for "Self-supervised edge features for improved Graph Neural Network training",

Self-supervised edge features for improved Graph Neural Network training Data availability: Here is a link to the raw data for the organoids dataset.

23 Dec 02, 2022

Code and project page for ICCV 2021 paper "DisUnknown: Distilling Unknown Factors for Disentanglement Learning"

DisUnknown: Distilling Unknown Factors for Disentanglement Learning See introduction on our project page Requirements PyTorch = 1.8.0 torch.linalg.ei

24 May 16, 2022

ML models and internal tensors 3D visualizer

The free Zetane Viewer is a tool to help understand and accelerate discovery in machine learning and artificial neural networks. It can be used to ope

787 Dec 30, 2022