FAT Forensics
FAT Forensics: A Python Toolbox for Implementing and Deploying Fairness, Accountability and Transparency Algorithms in Predictive Systems - Published in JOSS (2020)
shap
A game theoretic approach to explain the output of any machine learning model.
thetis
Service to examine data processing pipelines (e.g., machine learning or deep learning pipelines) for uncertainty consistency (calibration), fairness, and other safety-relevant aspects.
https://github.com/csinva/interpretable-embeddings
Interpretable text embeddings by asking LLMs yes/no questions (NeurIPS 2024)
hierarchical-dnn-interpretations
Using / reproducing ACD from the paper "Hierarchical interpretations for neural network predictions" 🧠 (ICLR 2019)
https://github.com/agamiko/gebi
GEBI: Global Explanations for Bias Identification. Open source code for discovering bias in data with skin lesion dataset
https://github.com/baldassarrefe/graph-network-explainability
Explainability techniques for Graph Networks, applied to a synthetic dataset and an organic chemistry task. Code for the workshop paper "Explainability Techniques for Graph Convolutional Networks" (ICML19)
model-guidance
Code for the paper: Studying How to Efficiently and Effectively Guide Models with Explanations. ICCV 2023.
3d-viz-score-cam
Visualizing 3D ResNet for Medical Image Classification With Score-CAM
https://github.com/cn-tu/adversarial-recurrent-ids
Contact: Alexander Hartl, Maximilian Bachl, Fares Meghdouri. Explainability methods and Adversarial Robustness metrics for RNNs for Intrusion Detection Systems. Also contains code for "SparseIDS: Learning Packet Sampling with Reinforcement Learning" (branch "rl").
https://github.com/birkhoffg/explainable-ml-papers
A list of research papers of explainable machine learning.
scene-representation-diffusion-model
Linear probe found representations of scene attributes in a text-to-image diffusion model
modeling-uncertainty-local-explainability
Local explanations with uncertainty 💐!
azimuth
Helping AI practitioners better understand their datasets and models in text classification. From ServiceNow.
https://github.com/ai4healthuol/causalconceptts
Repository for the paper 'CausalConceptTS: Causal Attributions for Time Series Classification using High Fidelity Diffusion Models'.
https://github.com/csinva/iprompt
Finding semantically meaningful and accurate prompts.
xsearchkg
Source code for XSearchKG, a full-stack web application for explainable keyword search over knowledge graphs
machine-learning-neural-python
Introduction to artificial neural nets with Python
https://github.com/csinva/transformation-importance
Using / reproducing TRIM from the paper "Transformation Importance with Applications to Cosmology" 🌌 (ICLR Workshop 2020)
talktomodel
TalkToModel gives anyone with the powers of XAI through natural language conversations 💬!
awesome-safety-critical-ai
When the stakes are high, intelligence is only half the equation - reliability is the other ⚠️
https://github.com/astrazeneca/awesome-shapley-value
Reading list for "The Shapley Value in Machine Learning" (JCAI 2022)
surrogates-tutorial
What and How of Machine Learning Transparency – ECML-PKDD 2020 Hands-on Tutorial
awesome-production-machine-learning
A curated list of awesome open source libraries to deploy, monitor, version and scale your machine learning