Supercharging Imbalanced Data Learning WithCausal Representation Transfer

Last update: May 02, 2022

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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.

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