ExCon: Explanation-driven Supervised Contrastive Learning

Last update: Nov 01, 2022

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Deep Learning ExCon

Overview

ExCon: Explanation-driven Supervised Contrastive Learning

Link to the paper: https://arxiv.org/pdf/2111.14271.pdf

Contributors of this repo:

Zhibo Zhang ([email protected])
Jongseong Jang ([email protected])
Ruiwen Li ([email protected])

Run ExCon:

python3 ExCon/main_supcon.py --epochs=200 --explainer="GradCAM" --dataset="cifar100" --batch_size=256 --method="Ex_SupCon" --learning_rate=0.5 --temp=0.1 --cosine --negative_pair=1 --validation=1 --background_anchor=0 --exp_epochs=0

If you use our code, please cite our paper:

@misc{zhang2021excon,
      title={ExCon: Explanation-driven Supervised Contrastive Learning for Image Classification},
      author={Zhibo Zhang and Jongseong Jang and Chiheb Trabelsi and Ruiwen Li and Scott Sanner and Yeonjeong Jeong and Dongsub Shim},
      year={2021},
      eprint={2111.14271},
      archivePrefix={arXiv},
      primaryClass={cs.CV}
}

Reference Repos:

[1] https://github.com/HobbitLong/SupContrast

ExCon: Explanation-driven Supervised Contrastive Learning

Related tags

Overview

ExCon: Explanation-driven Supervised Contrastive Learning

Link to the paper: https://arxiv.org/pdf/2111.14271.pdf

Contributors of this repo:

Run ExCon:

Reference Repos:

Owner

Zhibo (Darren) Zhang

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ExCon: Explanation-driven Supervised Contrastive Learning

Related tags

Overview

ExCon: Explanation-driven Supervised Contrastive Learning

Link to the paper: https://arxiv.org/pdf/2111.14271.pdf

Contributors of this repo:

Run ExCon:

Reference Repos:

Owner

Zhibo (Darren) Zhang

This repository contains several jupyter notebooks to help users learn to use neon, our deep learning framework

Facebook AI Image Similarity Challenge: Descriptor Track

Graph-based community clustering approach to extract protein domains from a predicted aligned error matrix

Aircraft design optimization made fast through modern automatic differentiation

Remote sensing change detection tool based on PaddlePaddle

Real-Time and Accurate Full-Body Multi-Person Pose Estimation&Tracking System

Sound-guided Semantic Image Manipulation - Official Pytorch Code (CVPR 2022)

PyTorch Implementation of Fully Convolutional Networks. (Training code to reproduce the original result is available.)

Reproduce ResNet-v2(Identity Mappings in Deep Residual Networks) with MXNet

Code release of paper Improving neural implicit surfaces geometry with patch warping

[AAAI2021] The source code for our paper 《Enhancing Unsupervised Video Representation Learning by Decoupling the Scene and the Motion》.

CSE-519---Project - Job Title Analysis (Project for CSE 519 - Data Science Fundamentals)

A simple approach to emable dense segmentation with ViT.

Multi-Target Adversarial Frameworks for Domain Adaptation in Semantic Segmentation

PyTorch implementation of UPFlow (unsupervised optical flow learning)

Deploy a ML inference service on a budget in less than 10 lines of code.

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