Awesome

ECRT: Energy-based Causal Representation Transfer

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

<a href="pdf/NeurIPS-2021-supercharging-imbalanced-data-learning-with-energy-based-contrastive-representation-transfer-Paper.pdf" class="image fit"><img src="pdf/workflow.png" alt=""></a>

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:

• MADE flow
• GCL learning