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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Add new citation: Numeroso et al.
opened by danilonumeroso 1Hi 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
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added GCExplainer
opened by sbonner0 1You 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.
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Added new references
opened by nomisto 0Two 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)
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Include one more paper from NeurIPS 2020
opened by joaquincabezas 0The 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.
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Overwhelming amount of papers
opened by joaquincabezas 1Hi, 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
Releases(v_00001)
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v_00001(Dec 2, 2021)
pytorch implementation of "Distilling a Neural Network Into a Soft Decision Tree"
Soft-Decision-Tree Soft-Decision-Tree is the pytorch implementation of Distilling a Neural Network Into a Soft Decision Tree, paper recently published
262 Dec 04, 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!
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Model analysis tools for TensorFlow
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1.2k Dec 26, 2022
JittorVis - Visual understanding of deep learning model.
JittorVis - Visual understanding of deep learning model.
182 Jan 06, 2023
An Empirical Review of Optimization Techniques for Quantum Variational Circuits
QVC Optimizer Review Code for the paper "An Empirical Review of Optimization Techniques for Quantum Variational Circuits". Each of the python files ca
5 Jun 28, 2022
Making decision trees competitive with neural networks on CIFAR10, CIFAR100, TinyImagenet200, Imagenet
Neural-Backed Decision Trees · Site · Paper · Blog · Video Alvin Wan, *Lisa Dunlap, *Daniel Ho, Jihan Yin, Scott Lee, Henry Jin, Suzanne Petryk, Sarah
556 Dec 20, 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
2.2k Dec 30, 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
1.9k Dec 30, 2022
Auralisation of learned features in CNN (for audio)
AuralisationCNN This repo is for an example of auralisastion of CNNs that is demonstrated on ISMIR 2015. Files auralise.py: includes all required func
39 Nov 19, 2022
⬛ Python Individual Conditional Expectation Plot Toolbox
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140 Dec 30, 2022
Lucid library adapted for PyTorch
Lucent PyTorch + Lucid = Lucent The wonderful Lucid library adapted for the wonderful PyTorch! Lucent is not affiliated with Lucid or OpenAI's Clarity
520 Dec 26, 2022
A Practical Debugging Tool for Training Deep Neural Networks
Cockpit is a visual and statistical debugger specifically designed for deep learning!
31 Aug 14, 2022
Visualization Toolbox for Long Short Term Memory networks (LSTMs)
Visualization Toolbox for Long Short Term Memory networks (LSTMs)
1.1k Jan 04, 2023
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
40 Dec 07, 2022
Interactive convnet features visualization for Keras
Quiver Interactive convnet features visualization for Keras The quiver workflow Video Demo Build your model in keras model = Model(...) Launch the vis
1.7k Dec 21, 2022
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”
735 Jan 05, 2023
A collection of research papers and software related to explainability in graph machine learning.
A collection of research papers and software related to explainability in graph machine learning.
1.9k Dec 26, 2022
Using / reproducing ACD from the paper "Hierarchical interpretations for neural network predictions" 🧠 (ICLR 2019)
Hierarchical neural-net interpretations (ACD) 🧠 Produces hierarchical interpretations for a single prediction made by a pytorch neural network. Offic
111 Jan 03, 2023
Interpretability and explainability of data and machine learning models
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Visualizer for neural network, deep learning, and machine learning models
Netron is a viewer for neural network, deep learning and machine learning models. Netron supports ONNX, TensorFlow Lite, Keras, Caffe, Darknet, ncnn,
20.9k Dec 28, 2022