innoisys/epu-cnn-torch

This is a PyTorch implementation of "E pluribus unum interpretable convolutional neural networks"

Language: Python - Size: 408 KB - Last synced at: 2 days ago - Pushed at: 2 days ago - Stars: 1 - Forks: 0

interpretml/interpret

Fit interpretable models. Explain blackbox machine learning.

Language: C++ - Size: 14.7 MB - Last synced at: 1 day ago - Pushed at: 16 days ago - Stars: 6,483 - Forks: 746

KevinBian107/L-CTP-MVP

MVP repository for L-CTP

Language: Python - Size: 8.42 MB - Last synced at: 3 days ago - Pushed at: 3 days ago - Stars: 0 - Forks: 0

ModelOriented/DALEX

moDel Agnostic Language for Exploration and eXplanation

Language: Python - Size: 798 MB - Last synced at: about 23 hours ago - Pushed at: 3 months ago - Stars: 1,420 - Forks: 168

mmschlk/shapiq

Shapley Interactions and Shapley Values for Machine Learning

Language: Python - Size: 309 MB - Last synced at: 4 days ago - Pushed at: 4 days ago - Stars: 514 - Forks: 34

arthur-batel/IMPACT

Repository contaning the original code of IMPACT algorithm, an interpretable model for multi-target predictions with multi-class outputs"

Language: Jupyter Notebook - Size: 17.9 MB - Last synced at: 4 days ago - Pushed at: 4 days ago - Stars: 6 - Forks: 0

pyladiesams/ai-in-finance-python-lecture-beginner-may2022

AI in Finance - Python interactive lecture for students studying Finance

Language: Jupyter Notebook - Size: 1.88 MB - Last synced at: 3 days ago - Pushed at: 4 days ago - Stars: 4 - Forks: 3

SelfExplainML/PiML-Toolbox

PiML (Python Interpretable Machine Learning) toolbox for model development & diagnostics

Language: Jupyter Notebook - Size: 250 MB - Last synced at: 4 days ago - Pushed at: about 1 month ago - Stars: 1,247 - Forks: 127

IBM/AutoPeptideML

AutoML system for building trustworthy peptide bioactivity predictors

Language: Python - Size: 48.7 MB - Last synced at: 4 days ago - Pushed at: 22 days ago - Stars: 28 - Forks: 2

bgreenwell/ebm

Explainable Boosting Machines

Language: R - Size: 44.5 MB - Last synced at: 3 days ago - Pushed at: 2 months ago - Stars: 3 - Forks: 1

Trustworthy-ML-Lab/ThinkEdit

An effective weight-editing method for mitigating overly short reasoning in LLMs, and a mechanistic study uncovering how reasoning length is encoded in the model’s representation space.

Language: Python - Size: 545 KB - Last synced at: 7 days ago - Pushed at: 7 days ago - Stars: 10 - Forks: 1

lopusz/awesome-interpretable-machine-learning

Language: Python - Size: 1.47 MB - Last synced at: 5 days ago - Pushed at: about 2 years ago - Stars: 916 - Forks: 139

JHoelli/Awesome-Time-Series-Explainability

A list of (post-hoc) XAI for time series

Size: 424 KB - Last synced at: 9 days ago - Pushed at: 8 months ago - Stars: 134 - Forks: 16

interpretml/DiCE

Generate Diverse Counterfactual Explanations for any machine learning model.

Language: Python - Size: 15.2 MB - Last synced at: 12 days ago - Pushed at: 6 months ago - Stars: 1,397 - Forks: 200

salesforce/OmniXAI

OmniXAI: A Library for eXplainable AI

Language: Jupyter Notebook - Size: 64.7 MB - Last synced at: 12 days ago - Pushed at: 10 months ago - Stars: 916 - Forks: 100

ssfgunner/IIS

[ICLR 2025 Spotlight] This is the official repository for our paper: ''Enhancing Pre-trained Representation Classifiability can Boost its Interpretability''.

Language: Python - Size: 2.89 MB - Last synced at: 14 days ago - Pushed at: 14 days ago - Stars: 15 - Forks: 0

zju-vipa/awesome-neural-trees

Introduction, selected papers and possible corresponding codes in our review paper "A Survey of Neural Trees"

Size: 1.66 MB - Last synced at: 1 day ago - Pushed at: over 2 years ago - Stars: 78 - Forks: 9

MarcelRobeer/explabox

Explore/examine/explain/expose your model with the explabox!

Language: Python - Size: 3.03 MB - Last synced at: 15 days ago - Pushed at: 15 days ago - Stars: 16 - Forks: 0

M-Nauta/ProtoTree

ProtoTrees: Neural Prototype Trees for Interpretable Fine-grained Image Recognition, published at CVPR2021

Language: Python - Size: 870 KB - Last synced at: 2 days ago - Pushed at: almost 3 years ago - Stars: 101 - Forks: 21

jphall663/awesome-machine-learning-interpretability

A curated list of awesome responsible machine learning resources.

Size: 4.45 MB - Last synced at: 16 days ago - Pushed at: 23 days ago - Stars: 3,770 - Forks: 599

ModelOriented/kernelshap

Different SHAP algorithms

Language: R - Size: 2.5 MB - Last synced at: 7 days ago - Pushed at: about 1 month ago - Stars: 47 - Forks: 7

roycmeghna/I-HOPE

I-HOPE — Interpretable Hierarchical mOdel for Personalized mEntal Health Prediction

Language: Python - Size: 97.7 KB - Last synced at: 17 days ago - Pushed at: 17 days ago - Stars: 0 - Forks: 0

mf-wu/HiBoFL

Hierarchy-boosted funnel learning for identifying semiconductors with ultralow lattice thermal conductivity

Language: Python - Size: 6.6 MB - Last synced at: 17 days ago - Pushed at: 17 days ago - Stars: 2 - Forks: 0

fzi-forschungszentrum-informatik/TSInterpret

An Open-Source Library for the interpretability of time series classifiers

Language: Python - Size: 200 MB - Last synced at: 8 days ago - Pushed at: 6 months ago - Stars: 133 - Forks: 14

ModelOriented/modelStudio

📍 Interactive Studio for Explanatory Model Analysis

Language: R - Size: 36.2 MB - Last synced at: 8 days ago - Pushed at: over 1 year ago - Stars: 332 - Forks: 32

ModelOriented/treeshap

Compute SHAP values for your tree-based models using the TreeSHAP algorithm

Language: R - Size: 19.7 MB - Last synced at: 13 days ago - Pushed at: 10 months ago - Stars: 84 - Forks: 24

ottenbreit-data-science/aplr

APLR builds predictive, interpretable regression and classification models using Automatic Piecewise Linear Regression. It often rivals tree-based methods in predictive accuracy while offering smoother and interpretable predictions.

Language: C++ - Size: 6.13 MB - Last synced at: 23 days ago - Pushed at: 23 days ago - Stars: 17 - Forks: 4

Cassie818/MsaPhylo

Learning the language of phylogeny with MSA Transformer

Language: Jupyter Notebook - Size: 40 MB - Last synced at: 24 days ago - Pushed at: 25 days ago - Stars: 1 - Forks: 0

DebeshJha/MDNet

Abdominal Organ Segmentation using Multi Decoder Network (MDNet) [Accepted at ICASSP 2025]

Language: Python - Size: 1.6 MB - Last synced at: 25 days ago - Pushed at: 25 days ago - Stars: 7 - Forks: 1

sergioburdisso/pyss3

A Python package implementing a new interpretable machine learning model for text classification (with visualization tools for Explainable AI :octocat:)

Language: Python - Size: 102 MB - Last synced at: about 15 hours ago - Pushed at: 4 months ago - Stars: 341 - Forks: 44

idealo/cnn-exposed 📦

🕵️‍♂️ Interpreting Convolutional Neural Network (CNN) Results.

Language: Jupyter Notebook - Size: 69.6 MB - Last synced at: 9 days ago - Pushed at: 5 months ago - Stars: 177 - Forks: 30

medoidai/interpretable-machine-learning-blog-notebooks

Notebook examples from "A Practical Overview of Interpretable Machine Learning" blog post.

Language: Jupyter Notebook - Size: 3.05 MB - Last synced at: 5 days ago - Pushed at: almost 3 years ago - Stars: 6 - Forks: 0

hbaniecki/compress-then-explain

Efficient and accurate explanation estimation with distribution compression (ICLR 2025 Spotlight)

Language: Python - Size: 1.25 MB - Last synced at: 29 days ago - Pushed at: 3 months ago - Stars: 7 - Forks: 1

explainX/explainx

Explainable AI framework for data scientists. Explain & debug any blackbox machine learning model with a single line of code. We are looking for co-authors to take this project forward. Reach out @ [email protected]

Language: Jupyter Notebook - Size: 61.3 MB - Last synced at: 28 days ago - Pushed at: 9 months ago - Stars: 430 - Forks: 56

pbiecek/xai_resources

Interesting resources related to XAI (Explainable Artificial Intelligence)

Language: R - Size: 13.2 MB - Last synced at: 28 days ago - Pushed at: almost 3 years ago - Stars: 825 - Forks: 138

gully/blase

Interpretable Machine Learning for astronomical spectroscopy in PyTorch and JAX

Language: Jupyter Notebook - Size: 28.9 MB - Last synced at: 25 days ago - Pushed at: 10 months ago - Stars: 27 - Forks: 7

ModelOriented/survex

Explainable Machine Learning in Survival Analysis

Language: R - Size: 309 MB - Last synced at: 5 days ago - Pushed at: 11 months ago - Stars: 111 - Forks: 10

solegalli/machine-learning-interpretability

Code repository for the online course Machine Learning Interpretability

Language: Jupyter Notebook - Size: 23.9 MB - Last synced at: 25 days ago - Pushed at: 7 months ago - Stars: 26 - Forks: 18

jrieke/cnn-interpretability

🏥 Visualizing Convolutional Networks for MRI-based Diagnosis of Alzheimer’s Disease

Language: Jupyter Notebook - Size: 61.5 MB - Last synced at: 4 days ago - Pushed at: almost 6 years ago - Stars: 170 - Forks: 50

pietrobarbiero/pytorch_explain

PyTorch Explain: Interpretable Deep Learning in Python.

Language: Jupyter Notebook - Size: 42.1 MB - Last synced at: about 1 month ago - Pushed at: 12 months ago - Stars: 154 - Forks: 14

daikikatsuragawa/awesome-counterfactual-explanations

This repository is a curated collection of information (keywords, papers, libraries, books, etc.) about counterfactual explanations🙃 Contributions are welcome! Our maintenance capacity is limited, so we highly appreciate pull requests.

Size: 12.7 KB - Last synced at: 5 days ago - Pushed at: over 2 years ago - Stars: 18 - Forks: 0

jphall663/interpretable_machine_learning_with_python

Examples of techniques for training interpretable ML models, explaining ML models, and debugging ML models for accuracy, discrimination, and security.

Language: Jupyter Notebook - Size: 34.7 MB - Last synced at: 28 days ago - Pushed at: 11 months ago - Stars: 676 - Forks: 207

nredell/ShapML.jl

A Julia package for interpretable machine learning with stochastic Shapley values

Language: Julia - Size: 529 KB - Last synced at: about 1 month ago - Pushed at: about 1 year ago - Stars: 90 - Forks: 8

vam-sin/riboclette

Transformers for ribosome density prediction

Language: Jupyter Notebook - Size: 137 MB - Last synced at: about 1 month ago - Pushed at: about 1 month ago - Stars: 0 - Forks: 0

Graph-COM/GSAT

[ICML 2022] Graph Stochastic Attention (GSAT) for interpretable and generalizable graph learning.

Language: Jupyter Notebook - Size: 1.57 MB - Last synced at: about 1 month ago - Pushed at: about 1 year ago - Stars: 167 - Forks: 22

Shakti-95/Data-and-Codes-for-Integrated-Design-Framework-for-Titanium-Aluminides-Through-Interpretable-ML

Data and Codes for Integrated Design Framework for Titanium Aluminides Through Interpretable Machine Learning

Language: Jupyter Notebook - Size: 30.9 MB - Last synced at: about 1 month ago - Pushed at: about 1 month ago - Stars: 0 - Forks: 0

salesforce/ETSformer

PyTorch code for ETSformer: Exponential Smoothing Transformers for Time-series Forecasting

Language: Python - Size: 459 KB - Last synced at: about 1 month ago - Pushed at: about 1 year ago - Stars: 274 - Forks: 44

pyartemis/artemis

A Python package with explanation methods for extraction of feature interactions from predictive models

Language: Jupyter Notebook - Size: 16.6 MB - Last synced at: 5 days ago - Pushed at: over 1 year ago - Stars: 30 - Forks: 0

hbaniecki/adversarial-explainable-ai

💡 Adversarial attacks on explanations and how to defend them

Size: 2.62 MB - Last synced at: about 2 months ago - Pushed at: 5 months ago - Stars: 314 - Forks: 48

sbartlett97/model-understanding

Playing around with understanding how different tokens affect the generation in LLMs

Language: Python - Size: 48.8 KB - Last synced at: about 1 month ago - Pushed at: about 2 months ago - Stars: 0 - Forks: 0

tpoisot/InterpretableSDMWithJulia

Slides for the "Interpretable SDM with Julia" workshop

Language: TeX - Size: 268 MB - Last synced at: 28 days ago - Pushed at: 6 months ago - Stars: 5 - Forks: 2

doncamilom/QuiremaTGADecomp

Decompose Thermo Gravimetrical Analysis (TGA) curves into simpler logistic curves representing mass-change events with a chemical interpretation. All of the analysis is performed with the TensorFlow library for the creation of a NN-analogous model and optimization.

Language: Jupyter Notebook - Size: 52.2 MB - Last synced at: about 2 months ago - Pushed at: over 4 years ago - Stars: 0 - Forks: 0

imatge-upc/SurvLIMEpy

Local interpretability for survival models

Language: Python - Size: 3.7 MB - Last synced at: 28 days ago - Pushed at: 12 months ago - Stars: 24 - Forks: 4

cair/convolutional-tsetlin-machine-tutorial

Tutorial on the Convolutional Tsetlin Machine

Language: Python - Size: 316 KB - Last synced at: 27 days ago - Pushed at: over 4 years ago - Stars: 53 - Forks: 13

alan-turing-institute/Intro-to-transparent-ML-course

An Introduction to Transparent Machine Learning

Language: Jupyter Notebook - Size: 17.6 MB - Last synced at: 5 days ago - Pushed at: over 1 year ago - Stars: 13 - Forks: 2

fbargaglistoffi/BCF-IV

Package for heterogeneous causal effects in the presence of imperfect compliance (e.g., instrumental variables, fuzzy regression discontinuity designs)

Language: R - Size: 1.45 MB - Last synced at: 29 days ago - Pushed at: about 1 year ago - Stars: 16 - Forks: 4

JBris/seldon-testing

Testing MLServer and Alibi

Language: Jupyter Notebook - Size: 4.7 MB - Last synced at: 2 months ago - Pushed at: 2 months ago - Stars: 1 - Forks: 0

FarnoushRJ/SymbolicXAI

Official Implementation of the Paper "Towards symbolic XAI – explanation through human understandable logical relationships between features"

Language: Jupyter Notebook - Size: 3.91 KB - Last synced at: 2 months ago - Pushed at: 2 months ago - Stars: 0 - Forks: 0

si-cim/cbc-aaai-2025

Deep CBC Models for Prototype Based Interpretability Benchmarks

Language: Python - Size: 1.65 MB - Last synced at: about 2 months ago - Pushed at: 2 months ago - Stars: 0 - Forks: 0

Klest94/Bellatrex

Building Explanations through a LocaLly AccuraTe Rule EXtractor

Language: Jupyter Notebook - Size: 215 MB - Last synced at: 5 days ago - Pushed at: 6 months ago - Stars: 10 - Forks: 2

gianlucatruda/quantified-sleep

Quantified Sleep: Machine learning techniques for observational n-of-1 studies.

Language: Jupyter Notebook - Size: 11.1 MB - Last synced at: 10 days ago - Pushed at: almost 4 years ago - Stars: 46 - Forks: 2

Animadversio/Neuronal_Feature_Attribution_Model

Feature Attribution methods for neurons and Evolution experiments

Language: Jupyter Notebook - Size: 4.13 MB - Last synced at: 2 months ago - Pushed at: 2 months ago - Stars: 0 - Forks: 0

Henrymachiyu/ProtoViT

This code implements ProtoViT, a novel approach that combines Vision Transformers with prototype-based learning to create interpretable image classification models. Our implementation provides both high accuracy and explainability through learned prototypes.

Language: Python - Size: 1010 KB - Last synced at: 2 months ago - Pushed at: 2 months ago - Stars: 17 - Forks: 6

mertkosan/GCFExplainer

Global Counterfactual Explainer for Graph Neural Networks

Language: Python - Size: 16.3 MB - Last synced at: about 2 months ago - Pushed at: about 2 years ago - Stars: 18 - Forks: 4

firmai/ml-fairness-framework

FairPut - Machine Learning Fairness Framework with LightGBM — Explainability, Robustness, Fairness (by @firmai)

Language: Jupyter Notebook - Size: 10.5 MB - Last synced at: 4 days ago - Pushed at: over 3 years ago - Stars: 71 - Forks: 16

schalkdaniel/compboost

C++ implementation and R API for componentwise boosting

Language: C++ - Size: 203 MB - Last synced at: about 6 hours ago - Pushed at: about 2 years ago - Stars: 23 - Forks: 3

rachtibat/zennit-crp

An eXplainable AI toolkit with Concept Relevance Propagation and Relevance Maximization

Language: Jupyter Notebook - Size: 17.9 MB - Last synced at: 21 days ago - Pushed at: 11 months ago - Stars: 124 - Forks: 18

MarekWadinger/adaptive-interpretable-ad

Self-Supervised Adaptive and Interpretable Anomaly Detection with Dynamic Operating Limits

Language: Python - Size: 158 MB - Last synced at: 2 months ago - Pushed at: 2 months ago - Stars: 5 - Forks: 0

Assaoka/Assaoka

Size: 38.1 KB - Last synced at: 8 days ago - Pushed at: 8 days ago - Stars: 5 - Forks: 0

runstats21/college-score-card-analysis

Language: Jupyter Notebook - Size: 39.6 MB - Last synced at: 3 months ago - Pushed at: 3 months ago - Stars: 0 - Forks: 0

dylan-slack/TalkToModel

TalkToModel gives anyone with the powers of XAI through natural language conversations 💬!

Language: Python - Size: 10.1 MB - Last synced at: 28 days ago - Pushed at: almost 2 years ago - Stars: 120 - Forks: 25

bgreenwell/fastshap

Fast approximate Shapley values in R

Language: R - Size: 99.4 MB - Last synced at: about 1 month ago - Pushed at: about 1 year ago - Stars: 119 - Forks: 18

jobregon1212/rulecosi

RuleCOSI is a machine learning package that combine and simplifies tree ensembles and generates a single rule-based classifier that is smaller and simpler.

Language: Python - Size: 173 KB - Last synced at: 2 months ago - Pushed at: 4 months ago - Stars: 8 - Forks: 2

deepfx/netlens

A toolkit for interpreting and analyzing neural networks (vision)

Language: Jupyter Notebook - Size: 130 MB - Last synced at: 6 days ago - Pushed at: almost 5 years ago - Stars: 26 - Forks: 2

davideferrari92/multiobjective_symbolic_regression

This is a Python library that implements a Multi-objective Symbolic Regression algorithm. It can be used as a Machine Learning algorithm to create predictive models in the form of mathematical expressions.

Language: Python - Size: 1.1 MB - Last synced at: about 1 month ago - Pushed at: 6 months ago - Stars: 17 - Forks: 5

adaamko/POTATO

XAI based human-in-the-loop framework for automatic rule-learning.

Language: Jupyter Notebook - Size: 6.07 MB - Last synced at: 7 days ago - Pushed at: 10 months ago - Stars: 48 - Forks: 8

donlapark/XLabel

XLabel: An Explainable Data Labeling Assistant

Language: Jupyter Notebook - Size: 2.84 MB - Last synced at: 3 days ago - Pushed at: about 2 years ago - Stars: 7 - Forks: 2

CPS-research-group/dtsemnet

Implementation of DTSemNet Architecture

Language: Python - Size: 40.6 MB - Last synced at: 3 months ago - Pushed at: 3 months ago - Stars: 4 - Forks: 0

jphall663/diabetes_use_case

Sample use case for Xavier AI in Healthcare conference: https://www.xavierhealth.org/ai-summit-day2/

Language: Jupyter Notebook - Size: 73.7 MB - Last synced at: about 1 month ago - Pushed at: 11 months ago - Stars: 27 - Forks: 13

ananthu-aniraj/pdiscoformer

[ECCV 2024 Oral] Official implementation of the paper "PDiscoFormer: Relaxing Part Discovery Constraints with Vision Transformers"

Language: Python - Size: 383 KB - Last synced at: 3 months ago - Pushed at: 3 months ago - Stars: 9 - Forks: 1

khalooei/LSA

LSA : Layer Sustainability Analysis framework for the analysis of layer vulnerability in a given neural network. LSA can be a helpful toolkit to assess deep neural networks and to extend the adversarial training approaches towards improving the sustainability of model layers via layer monitoring and analysis.

Language: Python - Size: 33.8 MB - Last synced at: 16 days ago - Pushed at: about 3 years ago - Stars: 17 - Forks: 6

fbargaglistoffi/NetworkCausalTree

Package for heterogeneous treatment and spillover effects under network interference

Language: R - Size: 1.81 MB - Last synced at: 4 months ago - Pushed at: 4 months ago - Stars: 7 - Forks: 3

keiserlab/plaquebox-paper

Repo for Tang et al, bioRxiv 454793 (2018)

Language: Jupyter Notebook - Size: 31.6 MB - Last synced at: about 1 month ago - Pushed at: about 6 years ago - Stars: 41 - Forks: 25

nredell/shapFlex

An R package for computing asymmetric Shapley values to assess causality in any trained machine learning model

Language: R - Size: 2.13 MB - Last synced at: 28 days ago - Pushed at: almost 5 years ago - Stars: 74 - Forks: 7

vanlalpeka/interpretable_AI

Exploring AI/ML/Data-science concepts

Language: Jupyter Notebook - Size: 771 KB - Last synced at: 4 months ago - Pushed at: 4 months ago - Stars: 0 - Forks: 0

TouradBaba/model_engineering

This repository hosts a machine learning tool for breast cancer classification, emphasizing model interpretability. It is deployed on Streamlit Cloud, with a PostgreSQL database for tracking results and data drift, and includes an automated retraining workflow.

Language: Jupyter Notebook - Size: 12.7 MB - Last synced at: 3 months ago - Pushed at: 4 months ago - Stars: 0 - Forks: 0

NielsenErik/Coach-QD-MARL

Interpretable Multi Agent Reinforcement Learning with a Quality DIversity Approach

Language: Python - Size: 964 MB - Last synced at: 4 months ago - Pushed at: 4 months ago - Stars: 0 - Forks: 0

pykale/transparentML

An Introduction to Transparent Machine Learning

Language: Jupyter Notebook - Size: 186 MB - Last synced at: about 1 month ago - Pushed at: over 1 year ago - Stars: 11 - Forks: 12

Linn39/gait_cnn

Repo to analyze time series data with Convolutional Neural Network (CNN) and use explainable AI methods to visualize feature importance.

Language: Python - Size: 1.51 MB - Last synced at: 4 months ago - Pushed at: 4 months ago - Stars: 0 - Forks: 1

aminaghoul/TrajDCM

Size: 683 KB - Last synced at: 4 months ago - Pushed at: 4 months ago - Stars: 2 - Forks: 0

thiswillbeyourgithub/repeng Fork of vgel/repeng

Repeng Research Fork - A library for making RepE control vectors

Language: Jupyter Notebook - Size: 392 KB - Last synced at: 4 months ago - Pushed at: 4 months ago - Stars: 2 - Forks: 0

cair/pyTsetlinMachineParallel

Multi-threaded implementation of the Tsetlin Machine, Convolutional Tsetlin Machine, Regression Tsetlin Machine, and Weighted Tsetlin Machine, with support for continuous features and multigranularity.

Language: C - Size: 290 KB - Last synced at: 27 days ago - Pushed at: over 2 years ago - Stars: 41 - Forks: 9

jphall663/jsm_2018_paper

Paper for 2018 Joint Statistical Meetings: https://ww2.amstat.org/meetings/jsm/2018/onlineprogram/AbstractDetails.cfm?abstractid=329539

Language: TeX - Size: 12.7 MB - Last synced at: about 1 month ago - Pushed at: over 6 years ago - Stars: 9 - Forks: 2

RishiDarkDevil/daam-i2i Fork of castorini/daam

Diffusion attentive attribution maps for interpreting Stable Diffusion for image-to-image attention.

Language: Python - Size: 30.3 MB - Last synced at: 4 months ago - Pushed at: 4 months ago - Stars: 49 - Forks: 1

deezer/functional_attribution

Code of our accepted ICML 2021 paper "Towards Rigorous Interpretations: a Formalisation of Feature Attribution" (D. Afchar, R. Hennequin, V. Guigue)

Language: Python - Size: 1.3 MB - Last synced at: about 1 month ago - Pushed at: almost 4 years ago - Stars: 7 - Forks: 1

alexanderepstein/NAVE

News Authentication Via Emotion

Language: Jupyter Notebook - Size: 26.8 MB - Last synced at: 3 months ago - Pushed at: over 2 years ago - Stars: 1 - Forks: 0

EloiZ/awesome-contrastive-explanation

A curated list of awesome contrastive explanation in ML resources

Size: 18.6 KB - Last synced at: 4 days ago - Pushed at: about 5 years ago - Stars: 4 - Forks: 0

SinaMohseni/Awesome-XAI-Evaluation

Reference tables to introduce and organize evaluation methods and measures for explainable machine learning systems

Size: 251 KB - Last synced at: 6 days ago - Pushed at: about 3 years ago - Stars: 74 - Forks: 10

tlverse/causalglm

Interpretable and model-robust causal inference for heterogeneous treatment effects using generalized linear working models with targeted machine-learning

Language: R - Size: 7.27 MB - Last synced at: about 2 months ago - Pushed at: about 3 years ago - Stars: 24 - Forks: 0

conorosully/interpreting-coastline-unet

Interpreting a U-Net used for coastal water body segmentation using permutation importance

Language: Jupyter Notebook - Size: 27.8 MB - Last synced at: 5 months ago - Pushed at: 5 months ago - Stars: 2 - Forks: 0