A collection of research papers and software related to explainability in graph machine learning.

Overview
Comments
  • Add new citation: Numeroso et al.

    Add new citation: Numeroso et al.

    Hi all, I've added a new reference to a paper of mine related to counterfactual explanations for molecule predictions. I hope this is appreciated :)

    Link to paper: https://arxiv.org/abs/2104.08060

    opened by danilonumeroso 1
  • added GCExplainer

    added GCExplainer

    You might want to double check this commit is ok - I added a new sub-heading called concept based methods which was not covered by the survey paper the rest of the approaches are categorised into.

    opened by sbonner0 1
  • Added new references

    Added new references

    Two papers on rule-based reasoning:

    • AnyBURL (Meilicke et. al)
    • SAFRAN (Ott et. al)

    And one application note on a web application for visualizing predictions and their explanations using made my the approaches above:

    • LinkExplorer (Ott et. al)
    opened by nomisto 0
  • Include one more paper from NeurIPS 2020

    Include one more paper from NeurIPS 2020

    The work 'Evaluating Attribution for Graph Neural Networks' is particularly useful because of its approach as a benchmarking. It comprises several attribution techniques and GNN architectures.

    opened by joaquincabezas 0
  • Overwhelming amount of papers

    Overwhelming amount of papers

    Hi, I have been impressed about how fast is this field growing. As I continue reading and learning, I will contribute with papers to make this list even better.

    In particular, @flyingdoog is maintaining a list with the papers (grouped by year) at https://github.com/flyingdoog/awesome-graph-explainability-papers that can be interesting to review

    opened by joaquincabezas 1
Owner
AstraZeneca
Data Science & AI: Unlocking new science insights
AstraZeneca
Python implementation of R package breakDown

pyBreakDown Python implementation of breakDown package (https://github.com/pbiecek/breakDown). Docs: https://pybreakdown.readthedocs.io. Requirements

MI^2 DataLab 41 Mar 17, 2022
🎆 A visualization of the CapsNet layers to better understand how it works

CapsNet-Visualization For more information on capsule networks check out my Medium articles here and here. Setup Use pip to install the required pytho

Nick Bourdakos 387 Dec 06, 2022
Lime: Explaining the predictions of any machine learning classifier

lime This project is about explaining what machine learning classifiers (or models) are doing. At the moment, we support explaining individual predict

Marco Tulio Correia Ribeiro 10.3k Jan 01, 2023
Code for "High-Precision Model-Agnostic Explanations" paper

Anchor This repository has code for the paper High-Precision Model-Agnostic Explanations. An anchor explanation is a rule that sufficiently “anchors”

Marco Tulio Correia Ribeiro 735 Jan 05, 2023
Delve is a Python package for analyzing the inference dynamics of your PyTorch model.

Delve is a Python package for analyzing the inference dynamics of your PyTorch model.

Delve 73 Dec 12, 2022
Pytorch Feature Map Extractor

MapExtrackt Convolutional Neural Networks Are Beautiful We all take our eyes for granted, we glance at an object for an instant and our brains can ide

Lewis Morris 40 Dec 07, 2022
A collection of infrastructure and tools for research in neural network interpretability.

Lucid Lucid is a collection of infrastructure and tools for research in neural network interpretability. We're not currently supporting tensorflow 2!

4.5k Jan 07, 2023
A python library for decision tree visualization and model interpretation.

dtreeviz : Decision Tree Visualization Description A python library for decision tree visualization and model interpretation. Currently supports sciki

Terence Parr 2.4k Jan 02, 2023
Model analysis tools for TensorFlow

TensorFlow Model Analysis TensorFlow Model Analysis (TFMA) is a library for evaluating TensorFlow models. It allows users to evaluate their models on

1.2k Dec 26, 2022
A data-driven approach to quantify the value of classifiers in a machine learning ensemble.

Documentation | External Resources | Research Paper Shapley is a Python library for evaluating binary classifiers in a machine learning ensemble. The

Benedek Rozemberczki 187 Dec 27, 2022
Algorithms for monitoring and explaining machine learning models

Alibi is an open source Python library aimed at machine learning model inspection and interpretation. The focus of the library is to provide high-qual

Seldon 1.9k Dec 30, 2022
Visualize a molecule and its conformations in Jupyter notebooks/lab using py3dmol

Mol Viewer This is a simple package wrapping py3dmol for a single command visualization of a RDKit molecule and its conformations (embed as Conformer

Benoît BAILLIF 1 Feb 11, 2022
Contrastive Explanation (Foil Trees), developed at TNO/Utrecht University

Contrastive Explanation (Foil Trees) Contrastive and counterfactual explanations for machine learning (ML) Marcel Robeer (2018-2020), TNO/Utrecht Univ

M.J. Robeer 41 Aug 29, 2022
Tool for visualizing attention in the Transformer model (BERT, GPT-2, Albert, XLNet, RoBERTa, CTRL, etc.)

Tool for visualizing attention in the Transformer model (BERT, GPT-2, Albert, XLNet, RoBERTa, CTRL, etc.)

Jesse Vig 4.7k Jan 01, 2023
treeinterpreter - Interpreting scikit-learn's decision tree and random forest predictions.

TreeInterpreter Package for interpreting scikit-learn's decision tree and random forest predictions. Allows decomposing each prediction into bias and

Ando Saabas 720 Dec 22, 2022
Code for visualizing the loss landscape of neural nets

Visualizing the Loss Landscape of Neural Nets This repository contains the PyTorch code for the paper Hao Li, Zheng Xu, Gavin Taylor, Christoph Studer

Tom Goldstein 2.2k Dec 30, 2022
Python Library for Model Interpretation/Explanations

Skater Skater is a unified framework to enable Model Interpretation for all forms of model to help one build an Interpretable machine learning system

Oracle 1k Dec 27, 2022
tensorboard for pytorch (and chainer, mxnet, numpy, ...)

tensorboardX Write TensorBoard events with simple function call. The current release (v2.1) is tested on anaconda3, with PyTorch 1.5.1 / torchvision 0

Tzu-Wei Huang 7.5k Jan 07, 2023
ModelChimp is an experiment tracker for Deep Learning and Machine Learning experiments.

ModelChimp What is ModelChimp? ModelChimp is an experiment tracker for Deep Learning and Machine Learning experiments. ModelChimp provides the followi

ModelChimp 124 Dec 21, 2022
An intuitive library to add plotting functionality to scikit-learn objects.

Welcome to Scikit-plot Single line functions for detailed visualizations The quickest and easiest way to go from analysis... ...to this. Scikit-plot i

Reiichiro Nakano 2.3k Dec 31, 2022