Code for Robust Contrastive Learning against Noisy Views

Related tags

Deep LearningRINCE
Overview

Robust Contrastive Learning against Noisy Views

This repository provides a PyTorch implementation of the Robust InfoNCE loss proposed in paper Robust Contrastive Learning against Noisy Views.

Requirements:

  • PyTorch >= 1.5.0

Pseudo Code

The implementation only requires a small modification to the InfoNCE code.

# bsz : batch size (number of positive pairs)
# pos : exponent for positive example, shape=[bsz]
# neg : sum of exponents for negative examples, shape=[bsz]
# q, lam : hyperparameters of RINCE

info_nce_loss = -log(pos / (pos + neg))
rince_loss = -pos**q / q + (lam * (pos + neg))**q / q

ImagNet Experiments

The code can be found in ImageNet/moco-v3 and ImageNet/simclr.

Citation

If you find this repo useful for your research, please consider citing the paper

@article{chuang2022robust,
  title={Robust Contrastive Learning against Noisy Views},
  author={Chuang, Ching-Yao and Hjelm, R Devon and Wang, Xin and Vineet, Vibhav and Joshi, Neel and Torralba, Antonio and Jegelka, Stefanie and Song, Yale},
  journal={arXiv preprint arXiv:2201.04309},
  year={2022}
}

For any questions, please contact Ching-Yao Chuang ([email protected]).

Owner
Ching-Yao Chuang
Ching-Yao Chuang
The software associated with a paper accepted at EMNLP 2021 titled "Open Knowledge Graphs Canonicalization using Variational Autoencoders".

Open-KG-canonicalization The software associated with a paper accepted at EMNLP 2021 titled "Open Knowledge Graphs Canonicalization using Variational

International Business Machines 13 Nov 11, 2022
Library of various Few-Shot Learning frameworks for text classification

FewShotText This repository contains code for the paper A Neural Few-Shot Text Classification Reality Check Environment setup # Create environment pyt

Thomas Dopierre 47 Jan 03, 2023
ByteTrack: Multi-Object Tracking by Associating Every Detection Box

ByteTrack ByteTrack is a simple, fast and strong multi-object tracker. ByteTrack: Multi-Object Tracking by Associating Every Detection Box Yifu Zhang,

Yifu Zhang 2.9k Jan 04, 2023
SOTA easy to use PyTorch-based DL training library

Easily train or fine-tune SOTA computer vision models from one training repository. SuperGradients Introduction Welcome to SuperGradients, a free open

619 Jan 03, 2023
This repository includes the official project for the paper: TransMix: Attend to Mix for Vision Transformers.

TransMix: Attend to Mix for Vision Transformers This repository includes the official project for the paper: TransMix: Attend to Mix for Vision Transf

Jie-Neng Chen 130 Jan 01, 2023
Code for paper "Do Language Models Have Beliefs? Methods for Detecting, Updating, and Visualizing Model Beliefs"

This is the codebase for the paper: Do Language Models Have Beliefs? Methods for Detecting, Updating, and Visualizing Model Beliefs Directory Structur

Peter Hase 19 Aug 21, 2022
Code and datasets for TPAMI 2021

SkeletonNet This repository constains the codes and ShapeNetV1-Surface-Skeleton,ShapNetV1-SkeletalVolume and 2d image datasets ShapeNetRendering. Plea

34 Aug 15, 2022
BuildingNet: Learning to Label 3D Buildings

BuildingNet This is the implementation of the BuildingNet architecture described in this paper: Paper: BuildingNet: Learning to Label 3D Buildings Arx

16 Nov 07, 2022
Unoffical reMarkable AddOn for Firefox.

reMarkable for Firefox (Download) This repo converts the offical reMarkable Chrome Extension into a Firefox AddOn published here under the name "Unoff

Jelle Schutter 45 Nov 28, 2022
Boostcamp AI Tech 3rd / Basic Paper reading w.r.t Embedding

Boostcamp AI Tech 3rd : Basic Paper Reading w.r.t Embedding TL;DR 1992년부터 2018년도까지 이루어진 word/sentence embedding의 중요한 줄기를 이루는 기초 논문 스터디를 진행하고자 합니다. 논

Soyeon Kim 14 Nov 14, 2022
An implementation of "MixHop: Higher-Order Graph Convolutional Architectures via Sparsified Neighborhood Mixing" (ICML 2019).

MixHop and N-GCN ⠀ A PyTorch implementation of "MixHop: Higher-Order Graph Convolutional Architectures via Sparsified Neighborhood Mixing" (ICML 2019)

Benedek Rozemberczki 393 Dec 13, 2022
ONNX Runtime Web demo is an interactive demo portal showing real use cases running ONNX Runtime Web in VueJS.

ONNX Runtime Web demo is an interactive demo portal showing real use cases running ONNX Runtime Web in VueJS. It currently supports four examples for you to quickly experience the power of ONNX Runti

Microsoft 58 Dec 18, 2022
source code for https://arxiv.org/abs/2005.11248 "Accelerating Antimicrobial Discovery with Controllable Deep Generative Models and Molecular Dynamics"

Accelerating Antimicrobial Discovery with Controllable Deep Generative Models and Molecular Dynamics This work will be published in Nature Biomedical

International Business Machines 71 Nov 15, 2022
A Probabilistic End-To-End Task-Oriented Dialog Model with Latent Belief States towards Semi-Supervised Learning

LABES This is the code for EMNLP 2020 paper "A Probabilistic End-To-End Task-Oriented Dialog Model with Latent Belief States towards Semi-Supervised L

17 Sep 28, 2022
Cross-Image Region Mining with Region Prototypical Network for Weakly Supervised Segmentation

Cross-Image Region Mining with Region Prototypical Network for Weakly Supervised Segmentation The code of: Cross-Image Region Mining with Region Proto

LiuWeide 16 Nov 26, 2022
Crossover Learning for Fast Online Video Instance Segmentation (ICCV 2021)

TL;DR: CrossVIS (Crossover Learning for Fast Online Video Instance Segmentation) proposes a novel crossover learning paradigm to fully leverage rich c

Hust Visual Learning Team 79 Nov 25, 2022
Code in PyTorch for the convex combination linear IAF and the Householder Flow, J.M. Tomczak & M. Welling

VAE with Volume-Preserving Flows This is a PyTorch implementation of two volume-preserving flows as described in the following papers: Tomczak, J. M.,

Jakub Tomczak 87 Dec 26, 2022
Developing your First ML Workflow of the AWS Machine Learning Engineer Nanodegree Program

Exercises and project documentation for the 3. Developing your First ML Workflow of the AWS Machine Learning Engineer Nanodegree Program

Simona Mircheva 1 Jan 13, 2022
A PyTorch Implementation of "Neural Arithmetic Logic Units"

Neural Arithmetic Logic Units [WIP] This is a PyTorch implementation of Neural Arithmetic Logic Units by Andrew Trask, Felix Hill, Scott Reed, Jack Ra

Kevin Zakka 181 Nov 18, 2022
A framework for analyzing computer vision models with simulated data

3DB: A framework for analyzing computer vision models with simulated data Paper Quickstart guide Blog post Installation Follow instructions on: https:

3DB 112 Jan 01, 2023