Official repository for: Continuous Control With Ensemble DeepDeterministic Policy Gradients

Related tags

Deep LearningED2
Overview

Continuous Control With Ensemble Deep Deterministic Policy Gradients

This repository is the official implementation of Continuous Control With Ensemble Deep Deterministic Policy Gradients.

image

Requirements

Before installation, please make sure you have MuJoCo engine set up on your machine. We use mujoco150 in order to be comparable with previous benchmarks on v2 environments. See this issue

To install requirements:

pip install -r requirements.txt

Training

To train the model(s) in the paper, run this command:

python run.py <experiment_specification path>

Logger automatically stops training and evaluates current policy every log_every environment interactions. The data is printed to standard output and stored on drive.

We include specifications for our most important experiments.

Path Description
specs/ed2_on_mujoco.py Benchmark of our method
specs/sac_on_mujoco.py Benchmark of our implementation of SAC
specs/sunrise_on_mujoco.py Benchmark of our implementation of SUNRISE
specc/sop_on_mujoco.py Benchmark of our implementation of SOP

Results

Our model achieves the following performance on the MuJoCo suite:

image

UNAVOIDS: Unsupervised and Nonparametric Approach for Visualizing Outliers and Invariant Detection Scoring

UNAVOIDS: Unsupervised and Nonparametric Approach for Visualizing Outliers and Invariant Detection Scoring Code Summary aggregate.py: this script aggr

1 Dec 28, 2021
Code for Multiple Instance Active Learning for Object Detection, CVPR 2021

MI-AOD Language: 简体中文 | English Introduction This is the code for Multiple Instance Active Learning for Object Detection (The PDF is not available tem

Tianning Yuan 269 Dec 21, 2022
Official Pytorch implementation for 2021 ICCV paper "Learning Motion Priors for 4D Human Body Capture in 3D Scenes" and trained models / data

Learning Motion Priors for 4D Human Body Capture in 3D Scenes (LEMO) Official Pytorch implementation for 2021 ICCV (oral) paper "Learning Motion Prior

165 Dec 19, 2022
An Ensemble of CNN (Python 3.5.1 Tensorflow 1.3 numpy 1.13)

An Ensemble of CNN (Python 3.5.1 Tensorflow 1.3 numpy 1.13)

0 May 06, 2022
Agent-based model simulator for air quality and pandemic risk assessment in architectural spaces

Agent-based model simulation for air quality and pandemic risk assessment in architectural spaces. User Guide archABM is a fast and open source agent-

Vicomtech 10 Dec 05, 2022
[NeurIPS 2021] Garment4D: Garment Reconstruction from Point Cloud Sequences

Garment4D [PDF] | [OpenReview] | [Project Page] Overview This is the codebase for our NeurIPS 2021 paper Garment4D: Garment Reconstruction from Point

Fangzhou Hong 112 Dec 23, 2022
[CVPR 2021] Unsupervised 3D Shape Completion through GAN Inversion

ShapeInversion Paper Junzhe Zhang, Xinyi Chen, Zhongang Cai, Liang Pan, Haiyu Zhao, Shuai Yi, Chai Kiat Yeo, Bo Dai, Chen Change Loy "Unsupervised 3D

100 Dec 22, 2022
Functional deep learning

Pipeline abstractions for deep learning. Full documentation here: https://lf1-io.github.io/padl/ PADL: is a pipeline builder for PyTorch. may be used

LF1 101 Nov 09, 2022
PyTorch Implementation of PIXOR: Real-time 3D Object Detection from Point Clouds

PIXOR: Real-time 3D Object Detection from Point Clouds This is a custom implementation of the paper from Uber ATG using PyTorch 1.0. It represents the

Philip Huang 270 Dec 14, 2022
BADet: Boundary-Aware 3D Object Detection from Point Clouds (Pattern Recognition 2022)

BADet: Boundary-Aware 3D Object Detection from Point Clouds (Pattern Recognition

Rui Qian 17 Dec 12, 2022
The official PyTorch code for NeurIPS 2021 ML4AD Paper, "Does Thermal data make the detection systems more reliable?"

MultiModal-Collaborative (MMC) Learning Framework for integrating RGB and Thermal spectral modalities This is the official code for NeurIPS 2021 Machi

NeurAI 12 Nov 02, 2022
This repo contains the official implementations of EigenDamage: Structured Pruning in the Kronecker-Factored Eigenbasis

EigenDamage: Structured Pruning in the Kronecker-Factored Eigenbasis This repo contains the official implementations of EigenDamage: Structured Prunin

Chaoqi Wang 107 Apr 20, 2022
Supervised domain-agnostic prediction framework for probabilistic modelling

A supervised domain-agnostic framework that allows for probabilistic modelling, namely the prediction of probability distributions for individual data

The Alan Turing Institute 112 Oct 23, 2022
Fully Automatic Page Turning on Real Scores

Fully Automatic Page Turning on Real Scores This repository contains the corresponding code for our extended abstract Henkel F., Schwaiger S. and Widm

Florian Henkel 7 Jan 02, 2022
This is an official implementation of "Polarized Self-Attention: Towards High-quality Pixel-wise Regression"

Polarized Self-Attention: Towards High-quality Pixel-wise Regression This is an official implementation of: Huajun Liu, Fuqiang Liu, Xinyi Fan and Don

DeLightCMU 212 Jan 08, 2023
✅ How Robust are Fact Checking Systems on Colloquial Claims?. In NAACL-HLT, 2021.

How Robust are Fact Checking Systems on Colloquial Claims? Official PyTorch implementation of our NAACL paper: Byeongchang Kim*, Hyunwoo Kim*, Seokhee

Byeongchang Kim 19 Mar 15, 2022
the code for our CVPR 2021 paper Bilateral Grid Learning for Stereo Matching Network [BGNet]

BGNet This repository contains the code for our CVPR 2021 paper Bilateral Grid Learning for Stereo Matching Network [BGNet] Environment Python 3.6.* C

3DCV developer 87 Nov 29, 2022
Imbalanced Gradients: A Subtle Cause of Overestimated Adversarial Robustness

Imbalanced Gradients: A Subtle Cause of Overestimated Adversarial Robustness Code for Paper "Imbalanced Gradients: A Subtle Cause of Overestimated Adv

Hanxun Huang 11 Nov 30, 2022
IJON is an annotation mechanism that analysts can use to guide fuzzers such as AFL.

IJON SPACE EXPLORER IJON is an annotation mechanism that analysts can use to guide fuzzers such as AFL. Using only a small (usually one line) annotati

Chair for Sys­tems Se­cu­ri­ty 146 Dec 16, 2022
CDGAN: Cyclic Discriminative Generative Adversarial Networks for Image-to-Image Transformation

CDGAN CDGAN: Cyclic Discriminative Generative Adversarial Networks for Image-to-Image Transformation CDGAN Implementation in PyTorch This is the imple

Kancharagunta Kishan Babu 6 Apr 19, 2022