Awesome Explainable Graph Reasoning
A collection of research papers and software related to explainability in graph machine learning.
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A collection of research papers and software related to explainability in graph machine learning.
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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
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.
Two papers on rule-based reasoning:
And one application note on a web application for visualizing predictions and their explanations using made my the approaches above:
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.
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
This repository contains a number of convolutional neural network visualization techniques implemented in PyTorch.
Netron is a viewer for neural network, deep learning and machine learning models. Netron supports ONNX (.onnx, .pb, .pbtxt), Keras (.h5, .keras), Tens
QVC Optimizer Review Code for the paper "An Empirical Review of Optimization Techniques for Quantum Variational Circuits". Each of the python files ca
Convolutional Neural Network Visualizations This repository contains a number of convolutional neural network visualization techniques implemented in
Neural-Backed Decision Trees · Site · Paper · Blog · Video Alvin Wan, *Lisa Dunlap, *Daniel Ho, Jihan Yin, Scott Lee, Henry Jin, Suzanne Petryk, Sarah
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
Yellowbrick Visual analysis and diagnostic tools to facilitate machine learning model selection. What is Yellowbrick? Yellowbrick is a suite of visual
Visualizing the Loss Landscape of Neural Nets This repository contains the PyTorch code for the paper Hao Li, Zheng Xu, Gavin Taylor, Christoph Studer
Lucent PyTorch + Lucid = Lucent The wonderful Lucid library adapted for the wonderful PyTorch! Lucent is not affiliated with Lucid or OpenAI's Clarity
A collection of research papers and software related to explainability in graph machine learning.
JittorVis - Visual understanding of deep learning model.
======== FairML: Auditing Black-Box Predictive Models FairML is a python toolbox auditing the machine learning models for bias. Description Predictive
Delve is a Python package for analyzing the inference dynamics of your PyTorch model.
GNNLens2 is an interactive visualization tool for graph neural networks (GNN).
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
Welcome to Scikit-plot Single line functions for detailed visualizations The quickest and easiest way to go from analysis... ...to this. Scikit-plot i
FlashTorch A Python visualization toolkit, built with PyTorch, for neural networks in PyTorch. Neural networks are often described as "black box". The
Class Activation Map methods implemented in Pytorch pip install grad-cam ⭐ Comprehensive collection of Pixel Attribution methods for Computer Vision.
ModelChimp What is ModelChimp? ModelChimp is an experiment tracker for Deep Learning and Machine Learning experiments. ModelChimp provides the followi
Mol Viewer This is a simple package wrapping py3dmol for a single command visualization of a RDKit molecule and its conformations (embed as Conformer