Proton density fat fraction calculation for MRI

PyTorch implementation of MoCo v3 https//arxiv.org/abs/2104.02057

Automating Detection and Severity Assessment of Atopic Dermatitis

Self-supervised learning for EEG

Self-supervised representation learning from 12-lead ECG data

Scripts and modules for training and testing neural network for ECG automatic classification. Companion code to the paper "Automatic diagnosis of the 12-lead ECG using a deep neural network".

Tools for training explainable models using attribution priors.

Mixture of Gaussian Processes Model for Sparse Longitudinal Data

State-of-the-Art Deep Learning scripts organized by models - easy to train and deploy with reproducible accuracy and performance on enterprise-grade infrastructure.

Surrogate Assisted Feature Extraction in R

Repository for NeurIPS 2020 Spotlight "AdaBelief Optimizer: Adapting stepsizes by the belief in observed gradients"

NumPy and Tensorflow implementation of the Multidimensional Contrast Limited Adaptive Histogram Equalization (MCLAHE) procedure

Weakly Supervised MRI Series Classification for the UK Biobank

Some code for processing and analysing UK Biobank cardiac MR images.

Code accompanying "Modelling the Distribution of 3D Brain MRI using a 2D Slice VAE"

Unsupervised Feature Learning via Non-parametric Instance Discrimination

Original implementation of Spatially Invariant Attend, Infer, Repeat (SPAIR) in TensorFlow.

Automated lung segmentation in CT

Advanced Statistical Computing at Vanderbilt University Medical Center's Department of Biostatistics

A PyTorch implementation of EfficientNet

A minimal PyTorch re-implementation of the OpenAI GPT (Generative Pretrained Transformer) training

Training codebase for our solution to Kaggle's Deepfake Detection Challenge

A prize winning solution for DFDC challenge

Open3D: A Modern Library for 3D Data Processing

Pytorch code for ICLR-20 Paper "Learning to Explore using Active Neural SLAM"

A curated list of papers & resources linked to 3D reconstruction from images.

A modern, C++-native, test framework for unit-tests, TDD and BDD - using C++14, C++17 and later (C++11 support is in v2.x branch, and C++03 on the Catch1.x branch)