explainable-ai
There are 1579 repositories under explainable-ai topic.
kmario23/deep-learning-drizzle
Drench yourself in Deep Learning, Reinforcement Learning, Machine Learning, Computer Vision, and NLP by learning from these exciting lectures!!
jacobgil/pytorch-grad-cam
Advanced AI Explainability for computer vision. Support for CNNs, Vision Transformers, Classification, Object detection, Segmentation, Image similarity and more.
interpretml/interpret
Fit interpretable models. Explain blackbox machine learning.
obss/sahi
Framework agnostic sliced/tiled inference + interactive ui + error analysis plots
microsoft/tensorwatch
Debugging, monitoring and visualization for Python Machine Learning and Data Science
MilesCranmer/PySR
High-Performance Symbolic Regression in Python and Julia
alan-ai/alan-sdk-web
The Self-Coding System for Your App — Alan AI SDK for Web
AstraZeneca/awesome-explainable-graph-reasoning
A collection of research papers and software related to explainability in graph machine learning.
Trusted-AI/AIX360
Interpretability and explainability of data and machine learning models
microsoft/responsible-ai-toolbox
Responsible AI Toolbox is a suite of tools providing model and data exploration and assessment user interfaces and libraries that enable a better understanding of AI systems. These interfaces and libraries empower developers and stakeholders of AI systems to develop and monitor AI more responsibly, and take better data-driven actions.
wangyongjie-ntu/Awesome-explainable-AI
A collection of research materials on explainable AI/ML
csinva/imodels
Interpretable ML package 🔍 for concise, transparent, and accurate predictive modeling (sklearn-compatible).
interpretml/DiCE
Generate Diverse Counterfactual Explanations for any machine learning model.
ModelOriented/DALEX
moDel Agnostic Language for Exploration and eXplanation (JMLR 2018; JMLR 2021)
cdpierse/transformers-interpret
Model explainability that works seamlessly with 🤗 transformers. Explain your transformers model in just 2 lines of code.
EthicalML/xai
XAI - An eXplainability toolbox for machine learning
valeman/awesome-conformal-prediction
A professionally curated list of awesome Conformal Prediction videos, tutorials, books, papers, PhD and MSc theses, articles and open-source libraries.
jacobgil/vit-explain
Explainability for Vision Transformers
DmitryRyumin/ICCV-2023-25-Papers
ICCV 2023-2025 Papers: Discover cutting-edge research from ICCV 2023-25, the leading computer vision conference. Stay updated on the latest in computer vision and deep learning, with code included. ⭐ support visual intelligence development!
salesforce/OmniXAI
OmniXAI: A Library for eXplainable AI
dswah/pyGAM
[CONTRIBUTORS WELCOME] Generalized Additive Models in Python
hila-chefer/Transformer-MM-Explainability
[ICCV 2021- Oral] Official PyTorch implementation for Generic Attention-model Explainability for Interpreting Bi-Modal and Encoder-Decoder Transformers, a novel method to visualize any Transformer-based network. Including examples for DETR, VQA.
aerdem4/lofo-importance
Leave One Feature Out Importance
maelfabien/Machine_Learning_Tutorials
Code, exercises and tutorials of my personal blog ! 📝
castorini/daam
Diffusion attentive attribution maps for interpreting Stable Diffusion.
flyingdoog/awesome-graph-explainability-papers
Papers about explainability of GNNs
MilesCranmer/SymbolicRegression.jl
Distributed High-Performance Symbolic Regression in Julia
Renumics/awesome-open-data-centric-ai
Curated list of open source tooling for data-centric AI on unstructured data.
deel-ai/xplique
👋 Xplique is a Neural Networks Explainability Toolbox
privacytrustlab/ml_privacy_meter
Privacy Meter: An open-source library to audit data privacy in statistical and machine learning algorithms.
mmschlk/shapiq
Shapley Interactions and Shapley Values for Machine Learning
understandable-machine-intelligence-lab/Quantus
Quantus is an eXplainable AI toolkit for responsible evaluation of neural network explanations
ScalaConsultants/Aspect-Based-Sentiment-Analysis
💭 Aspect-Based-Sentiment-Analysis: Transformer & Explainable ML (TensorFlow)
linkedin/FastTreeSHAP
Fast SHAP value computation for interpreting tree-based models
Cartus/Automated-Fact-Checking-Resources
Links to conference/journal publications in automated fact-checking (resources for the TACL22/EMNLP23 paper).