NovelD: A Simple yet Effective Exploration Criterion

Related tags

Deep LearningNovelD
Overview

NovelD: A Simple yet Effective Exploration Criterion

Intro

This is an implementation of the method proposed in

NovelD: A Simple yet Effective Exploration Criterion and BeBold: Exploration Beyond the Boundary of Explored Regions

Citation

If you use this code in your own work, please cite our paper:

@article{zhang2021noveld,
  title={NovelD: A Simple yet Effective Exploration Criterion},
  author={Zhang, Tianjun and Xu, Huazhe and Wang, Xiaolong and Wu, Yi and Keutzer, Kurt and Gonzalez, Joseph E and Tian, Yuandong},
  journal={Advances in Neural Information Processing Systems},
  volume={34},
  year={2021}
}

or

@article{zhang2020bebold,
  title={BeBold: Exploration Beyond the Boundary of Explored Regions},
  author={Zhang, Tianjun and Xu, Huazhe and Wang, Xiaolong and Wu, Yi and Keutzer, Kurt and Gonzalez, Joseph E and Tian, Yuandong},
  journal={arXiv preprint arXiv:2012.08621},
  year={2020}
}

Installation

# Install Instructions
conda create -n ride python=3.7
conda activate noveld 
git clone [email protected]:tianjunz/NovelD.git
cd NovelD
pip install -r requirements.txt

Train NovelD on MiniGrid

OMP_NUM_THREADS=1 python main.py --model bebold --env MiniGrid-ObstructedMaze-2Dlhb-v0 --total_frames 500000000 --intrinsic_reward_coef 0.05 --entropy_cost 0.0005

Acknowledgements

Our vanilla RL algorithm is based on RIDE.

License

This code is under the CC-BY-NC 4.0 (Attribution-NonCommercial 4.0 International) license.

StarGAN - Official PyTorch Implementation (CVPR 2018)

StarGAN: Unified Generative Adversarial Networks for Multi-Domain Image-to-Image Translation

Yunjey Choi 5.1k Dec 30, 2022
SemiNAS: Semi-Supervised Neural Architecture Search

SemiNAS: Semi-Supervised Neural Architecture Search This repository contains the code used for Semi-Supervised Neural Architecture Search, by Renqian

Renqian Luo 21 Aug 31, 2022
Tools for computational pathology

A toolkit for computational pathology and machine learning. View documentation Please cite our paper Installation There are several ways to install Pa

254 Dec 12, 2022
Pytorch implementation of

EfficientTTS Unofficial Pytorch implementation of "EfficientTTS: An Efficient and High-Quality Text-to-Speech Architecture"(arXiv). Disclaimer: Somebo

Liu Songxiang 109 Nov 16, 2022
PERIN is Permutation-Invariant Semantic Parser developed for MRP 2020

PERIN: Permutation-invariant Semantic Parsing David Samuel & Milan Straka Charles University Faculty of Mathematics and Physics Institute of Formal an

ÚFAL 40 Jan 04, 2023
Model Zoo for MindSpore

Welcome to the Model Zoo for MindSpore In order to facilitate developers to enjoy the benefits of MindSpore framework, we will continue to add typical

MindSpore 226 Jan 07, 2023
Focal and Global Knowledge Distillation for Detectors

FGD Paper: Focal and Global Knowledge Distillation for Detectors Install MMDetection and MS COCO2017 Our codes are based on MMDetection. Please follow

Mesopotamia 261 Dec 23, 2022
bespoke tooling for offensive security's Windows Usermode Exploit Dev course (OSED)

osed-scripts bespoke tooling for offensive security's Windows Usermode Exploit Dev course (OSED) Table of Contents Standalone Scripts egghunter.py fin

epi 268 Jan 05, 2023
Trajectory Prediction with Graph-based Dual-scale Context Fusion

DSP: Trajectory Prediction with Graph-based Dual-scale Context Fusion Introduction This is the project page of the paper Lu Zhang, Peiliang Li, Jing C

HKUST Aerial Robotics Group 103 Jan 04, 2023
A bare-bones TensorFlow framework for Bayesian deep learning and Gaussian process approximation

Aboleth A bare-bones TensorFlow framework for Bayesian deep learning and Gaussian process approximation [1] with stochastic gradient variational Bayes

Gradient Institute 127 Dec 12, 2022
Hand Gesture Volume Control | Open CV | Computer Vision

Gesture Volume Control Hand Gesture Volume Control | Open CV | Computer Vision Use gesture control to change the volume of a computer. First we look i

Jhenil Parihar 3 Jun 15, 2022
TriMap: Large-scale Dimensionality Reduction Using Triplets

TriMap TriMap is a dimensionality reduction method that uses triplet constraints to form a low-dimensional embedding of a set of points. The triplet c

Ehsan Amid 235 Dec 24, 2022
This is implementation of AlexNet(2012) with 3D Convolution on TensorFlow (AlexNet 3D).

AlexNet_3dConv TensorFlow implementation of AlexNet(2012) by Alex Krizhevsky, with 3D convolutiional layers. 3D AlexNet Network with a standart AlexNe

Denis Timonin 41 Jan 16, 2022
[AAAI22] Reliable Propagation-Correction Modulation for Video Object Segmentation

Reliable Propagation-Correction Modulation for Video Object Segmentation (AAAI22) Preview version paper of this work is available at: https://arxiv.or

Xiaohao Xu 70 Dec 04, 2022
Extracting and filtering paraphrases by bridging natural language inference and paraphrasing

nli2paraphrases Source code repository accompanying the preprint Extracting and filtering paraphrases by bridging natural language inference and parap

Matej Klemen 1 Mar 09, 2022
The first machine learning framework that encourages learning ML concepts instead of memorizing class functions.

SeaLion is designed to teach today's aspiring ml-engineers the popular machine learning concepts of today in a way that gives both intuition and ways of application. We do this through concise algori

Anish 324 Dec 27, 2022
Official source code of paper 'IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo'

IterMVS official source code of paper 'IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo' Introduction IterMVS is a novel lear

Fangjinhua Wang 127 Jan 04, 2023
Instance-level Image Retrieval using Reranking Transformers

Instance-level Image Retrieval using Reranking Transformers Fuwen Tan, Jiangbo Yuan, Vicente Ordonez, ICCV 2021. Abstract Instance-level image retriev

UVA Computer Vision 87 Jan 03, 2023
Official implementation of "Learning Not to Reconstruct" (BMVC 2021)

Official PyTorch implementation of "Learning Not to Reconstruct Anomalies" This is the implementation of the paper "Learning Not to Reconstruct Anomal

Marcella Astrid 13 Dec 04, 2022
This is an official implementation for "PlaneRecNet".

PlaneRecNet This is an official implementation for PlaneRecNet: A multi-task convolutional neural network provides instance segmentation for piece-wis

yaxu 50 Nov 17, 2022