Supercharging Imbalanced Data Learning WithCausal Representation Transfer

Last update: May 02, 2022

Related tags

Deep Learning ECRT

Overview

ECRT: Energy-based Causal Representation Transfer

Code for Supercharging Imbalanced Data Learning With Energy-basedContrastive Representation Transfer (NeurIPS 2021)

Model

Prerequisites

The algorithm is built with:

Python (version 3.7 or higher)
Numpy (version 1.16 or higher)
PyTorch (version 1.3.1)

Clone the repository, e.g.:

git clone https://github.com/ZidiXiu/ECRT.git

Running the Toy Dataset

Here we present a toy synthetic dataset

python train train_CRT_toy.py

When building the CRT framework, we referenced the following sources:

Owner

Zidi Xiu

A 4th year Ph.D. student in Biostatistics at Duke University, focusing on solving healthcare problems with machine learning and deep learning methods.

GitHub Repository

Robust fine-tuning of zero-shot models

Robust fine-tuning of zero-shot models This repository contains code for the paper Robust fine-tuning of zero-shot models by Mitchell Wortsman*, Gabri

224 Dec 29, 2022

structured-generative-modeling

This repository contains the implementation for the paper Information Theoretic StructuredGenerative Modeling, Specially thanks for the open-source co

0 Oct 11, 2021

GNN-based Recommendation Benchma

GRecX A Fair Benchmark for GNN-based Recommendation Preliminary Comparison DiffNet-Yelp dataset (featureless) Algo 73 Oct 17, 2022

Spectral normalization (SN) is a widely-used technique for improving the stability and sample quality of Generative Adversarial Networks (GANs)

Why Spectral Normalization Stabilizes GANs: Analysis and Improvements [paper (NeurIPS 2021)] [paper (arXiv)] [code] Authors: Zinan Lin, Vyas Sekar, Gi

32 Dec 16, 2022

This is the code of "Multi-view Contrastive Graph Clustering" in NeurlPS 2021.

MCGC Description This is the code of "Multi-view Contrastive Graph Clustering" in NeurlPS 2021. Datasets Results ACM DBLP IMDB Amazon photos Amazon co

31 Nov 14, 2022

Semantic segmentation models, datasets and losses implemented in PyTorch.

Semantic Segmentation in PyTorch Semantic Segmentation in PyTorch Requirements Main Features Models Datasets Losses Learning rate schedulers Data augm

1.3k Jan 07, 2023

thundernet ncnn

MMDetection_Lite 基于mmdetection 实现一些轻量级检测模型，安装方式和mmdeteciton相同 voc0712 voc 0712训练 voc2007测试 coco预训练 thundernet_voc_shufflenetv2_1.5 input shape mAP 320

39 Dec 05, 2022

A PyTorch Extension: Tools for easy mixed precision and distributed training in Pytorch

Introduction This is a Python package available on PyPI for NVIDIA-maintained utilities to streamline mixed precision and distributed training in Pyto

5 Sep 29, 2021

Code for "Neural Body: Implicit Neural Representations with Structured Latent Codes for Novel View Synthesis of Dynamic Humans" CVPR 2021 best paper candidate

News 05/17/2021 To make the comparison on ZJU-MoCap easier, we save quantitative and qualitative results of other methods at here, including Neural Vo

748 Jan 07, 2023

Implementation based on Paper - Learning a Probabilistic Latent Space of Object Shapes via 3D Generative-Adversarial Modeling

3 Jul 08, 2022

Pre-training of Graph Augmented Transformers for Medication Recommendation

G-Bert Pre-training of Graph Augmented Transformers for Medication Recommendation Intro G-Bert combined the power of Graph Neural Networks and BERT (B

101 Dec 27, 2022

AI Summer's complete catalog of articles

Learn Deep Learning with AI Summer A collection of all articles (almost 100) written for the AI Summer blog organized by topic. Deep Learning Theory M

95 Dec 29, 2022

Maximum Spatial Perturbation for Image-to-Image Translation (Official Implementation)

MSPC for I2I This repository is by Yanwu Xu and contains the PyTorch source code to reproduce the experiments in our CVPR2022 paper Maximum Spatial Pe

51 Dec 14, 2022

Tensorflow Implementation of ECCV'18 paper: Multimodal Human Motion Synthesis

MT-VAE for Multimodal Human Motion Synthesis This is the code for ECCV 2018 paper MT-VAE: Learning Motion Transformations to Generate Multimodal Human

36 Oct 02, 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

imbalanced-DL: Deep Imbalanced Learning in Python

imbalanced-DL: Deep Imbalanced Learning in Python Overview imbalanced-DL (imported as imbalanceddl) is a Python package designed to make deep imbalanc

19 Dec 28, 2022

Unofficial implementation of "Coordinate Attention for Efficient Mobile Network Design"

Unofficial implementation of "Coordinate Attention for Efficient Mobile Network Design". CoordAttention tensorflow slim

9 Aug 22, 2022

Conditional Generative Adversarial Networks (CGAN) for Mobility Data Fusion

This code implements the paper, Kim et al. (2021). Imputing Qualitative Attributes for Trip Chains Extracted from Smart Card Data Using a Conditional Generative Adversarial Network. Transportation Re

2 Feb 03, 2022

Group Fisher Pruning for Practical Network Compression(ICML2021)

Group Fisher Pruning for Practical Network Compression (ICML2021) By Liyang Liu*, Shilong Zhang*, Zhanghui Kuang, Jing-Hao Xue, Aojun Zhou, Xinjiang W

129 Dec 13, 2022

Deeper DCGAN with AE stabilization

AEGeAN Deeper DCGAN with AE stabilization Parallel training of generative adversarial network as an autoencoder with dedicated losses for each stage.

36 Feb 17, 2022