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202105-16-scrna-counterfactual

advosights_amplification_factor

advosights_influence_prediction

agile_data_code_2

Code for Agile Data Science 2.0, O'Reilly 2017, Second Edition

alibi

Algorithms for explaining machine learning models

awesome-diffusion-models

A collection of resources and papers on Diffusion Models

awesome-explainable-ai

A collection of research materials on explainable AI/ML

awesome-normalizing-flows

A list of awesome resources on normalizing flows.

awesome-single-cell

Community-curated list of software packages and data resources for single-cell, including RNA-seq, ATAC-seq, etc.

bavaria-quebec

Bavaria (TUM) and Quebec (Polytechnique) collaboration on a project on spinal cord MS lesion segmentation.

biopython

Official git repository for Biopython (originally converted from CVS)

bioseq-gfn-al

Code for "Biological Sequence Design with GFlowNets", 2022

bondgraphs.jl

Julia implementation of the bond graph framework

causal-imputation-synthetic-interventions

causal-ml

Must-read papers and resources related to causal inference and machine (deep) learning

chemcpa

Code for "Predicting Cellular Responses to Novel Drug Perturbations at a Single-Cell Resolution", NeurIPS 2022.

cimla

Counterfactual Inference by Machine Learning and Attribution Models

cinema-ot

classifier-free-guidance-pytorch

Implementation of Classifier Free Guidance in Pytorch, with emphasis on text conditioning, and flexibility to include multiple text embedding models

comp551-notebooks

Code provided for the Applied Machine Learning course (COMP 551)

continuous-gfn

counterfactual_generative_networks

[ICLR'21] Counterfactual Generative Networks

counterfactualms

counterfactuals for magnetic resonance images of multiple sclerosis

countergan

countrgan

Adversarial Defense using Generative Adversarial Networks

crawling-from-scratch

Repository for the Mastering Web Scraping in Python: Crawling from Scratch blogpost with the final code.

csl-with-selection

cvae-gan-zoos-pytorch-beginner

For beginner, this will be the best start for VAEs, GANs, and CVAE-GAN. This contains AE, DAE, VAE, GAN, CGAN, DCGAN, WGAN, WGAN-GP, VAE-GAN, CVAE-GAN. All use PyTorch.

d2l-en

Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 400 universities from 60 countries including Stanford, MIT, Harvard, and Cambridge.

ddpm-pytorch

This repo implements Denoising Diffusion Probabilistic Models (DDPM) in Pytorch