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202105-16-scrna-counterfactual

ace

This repository contains the official code for the CVPR 2023 paper ``Adversarial Counterfactual Visual Explanations''

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

artifact-eraser

Code for ICME 2024 paper COUNTERFACTUAL EXPLANATIONS FOR FACE FORGERY DETECTION VIA ADVERSARIAL REMOVAL OF ARTIFACTS

attentionpert

automaticweightedloss

Multi-task learning using uncertainty to weigh losses for scene geometry and semantics, Auxiliary Tasks in Multi-task Learning

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

calibrated_explanations

Repository for the explanation method Calibrated Explanations (CE)

carla

CARLA: A Python Library to Benchmark Algorithmic Recourse and Counterfactual Explanation Algorithms

causal-bald

causal-imputation-synthetic-interventions

causal-ml

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

causation-incomputervision

The repository contains lists of papers on causality and how relevant techniques are being used to further enhance deep learning era computer vision solutions.

cbed

Official implementation of the paper "Interventions, Where and How? Experimental Design for Causal Models at Scale", NeurIPS 2022.

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

codex

COunterfactual Deep learning for the in-silico EXploration of cancer cell line perturbations

comp551-notebooks

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