Supercharging Imbalanced Data Learning WithCausal Representation Transfer

Related tags

Deep LearningECRT
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.
Zidi Xiu
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