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
CellRank's reproducibility repository.

CellRank's reproducibility repository We believe that reproducibility is key and have made it as simple as possible to reproduce our results. Please e

Theis Lab 8 Oct 08, 2022
Running AlphaFold2 (from ColabFold) in Azure Machine Learning

Running AlphaFold2 (from ColabFold) in Azure Machine Learning Colby T. Ford, Ph.D. Companion repository for Medium Post: How to predict many protein s

Colby T. Ford 3 Feb 18, 2022
Official implementation of the paper 'High-Resolution Photorealistic Image Translation in Real-Time: A Laplacian Pyramid Translation Network' in CVPR 2021

LPTN Paper | Supplementary Material | Poster High-Resolution Photorealistic Image Translation in Real-Time: A Laplacian Pyramid Translation Network Ji

372 Dec 26, 2022
Newt - a Gaussian process library in JAX.

Newt __ \/_ (' \`\ _\, \ \\/ /`\/\ \\ \ \\

AaltoML 0 Nov 02, 2021
The final project of "Applying AI to 2D Medical Imaging Data" of "AI for Healthcare" nanodegree - Udacity.

Pneumonia Detection from X-Rays Project Overview In this project, you will apply the skills that you have acquired in this 2D medical imaging course t

Omar Laham 1 Jan 14, 2022
Distributionally robust neural networks for group shifts

Distributionally Robust Neural Networks for Group Shifts: On the Importance of Regularization for Worst-Case Generalization This code implements the g

151 Dec 25, 2022
An implementation of the Contrast Predictive Coding (CPC) method to train audio features in an unsupervised fashion.

CPC_audio This code implements the Contrast Predictive Coding algorithm on audio data, as described in the paper Unsupervised Pretraining Transfers we

8 Nov 14, 2022
A small library for doing fluid simulation with neural networks.

Neural Fluid Fields This is a small library for doing fluid simulation with neural fields. Check out our review paper, Neural Fields in Visual Computi

Towaki 23 Jun 23, 2022
Repository for the electrical and ICT benchmark model developed in the ERIGrid 2.0 project.

Benchmark Model Electrical and ICT System This repository contains the documentation, code, and models for the electrical and ICT benchmark model deve

ERIGrid 2.0 1 Nov 29, 2021
Pseudo-Visual Speech Denoising

Pseudo-Visual Speech Denoising This code is for our paper titled: Visual Speech Enhancement Without A Real Visual Stream published at WACV 2021. Autho

Sindhu 94 Oct 22, 2022
(CVPR 2022) Pytorch implementation of "Self-supervised transformers for unsupervised object discovery using normalized cut"

(CVPR 2022) TokenCut Pytorch implementation of Tokencut: Self-supervised Transformers for Unsupervised Object Discovery using Normalized Cut Yangtao W

YANGTAO WANG 200 Jan 02, 2023
Unofficial Implementation of Oboe (SIGCOMM'18').

Oboe-Reproduce This is the unofficial implementation of the paper "Oboe: Auto-tuning video ABR algorithms to network conditions, Zahaib Akhtar, Yun Se

Tianchi Huang 13 Nov 04, 2022
Everything you need to know about NumPy( Creating Arrays, Indexing, Math,Statistics,Reshaping).

Everything you need to know about NumPy( Creating Arrays, Indexing, Math,Statistics,Reshaping).

1 Feb 14, 2022
PyTorch implementation of "Conformer: Convolution-augmented Transformer for Speech Recognition" (INTERSPEECH 2020)

PyTorch implementation of Conformer: Convolution-augmented Transformer for Speech Recognition. Transformer models are good at capturing content-based

Soohwan Kim 565 Jan 04, 2023
Implementation of CVAE. Trained CVAE on faces from UTKFace Dataset to produce synthetic faces with a given degree of happiness/smileyness.

Conditional Smiles! (SmileCVAE) About Implementation of AE, VAE and CVAE. Trained CVAE on faces from UTKFace Dataset. Using an encoding of the Smile-s

Raúl Ortega 3 Jan 09, 2022
Link prediction using Multiple Order Local Information (MOLI)

Understanding the network formation pattern for better link prediction Authors: [e

Wu Lab 0 Oct 18, 2021
Megaverse is a new 3D simulation platform for reinforcement learning and embodied AI research

Megaverse Megaverse is a new 3D simulation platform for reinforcement learning and embodied AI research. The efficient design of the engine enables ph

Aleksei Petrenko 191 Dec 23, 2022
StarGAN - Official PyTorch Implementation (CVPR 2018)

StarGAN: Unified Generative Adversarial Networks for Multi-Domain Image-to-Image Translation

Yunjey Choi 5.1k Dec 30, 2022
PAWS 🐾 Predicting View-Assignments with Support Samples

This repo provides a PyTorch implementation of PAWS (predicting view assignments with support samples), as described in the paper Semi-Supervised Learning of Visual Features by Non-Parametrically Pre

Facebook Research 437 Dec 23, 2022
Pytorch implementation of our paper under review — Lottery Jackpots Exist in Pre-trained Models

Lottery Jackpots Exist in Pre-trained Models (Paper Link) Requirements Python = 3.7.4 Pytorch = 1.6.1 Torchvision = 0.4.1 Reproduce the Experiment

Yuxin Zhang 27 Jun 28, 2022