Quantifying Explainers of Graph Neural Networks in Computational Pathology

25 November 2020

Guillaume Jaume

Pushpak Pati

Behzad Bozorgtabar

Antonio Foncubierta-Rodríguez

Jean-Philippe Thiran

Papers citing "Quantifying Explainers of Graph Neural Networks in Computational Pathology"

43 / 43 papers shown

Title
Hierarchical Graph Representations in Digital Pathology Pushpak Pati Guillaume Jaume A. Foncubierta Florinda Feroce A. Anniciello ... G. Botti Jean-Philippe Thiran Maria Frucci O. Goksel M. Gabrani 44 120 0 22 Feb 2021
On quantitative aspects of model interpretability An-phi Nguyen María Rodríguez Martínez 43 114 0 15 Jul 2020
HACT-Net: A Hierarchical Cell-to-Tissue Graph Neural Network for Histopathological Image Classification Pushpak Pati Guillaume Jaume Lauren Alisha Fernandes A. Foncubierta Florinda Feroce ... G. Botti O. Goksel Jean-Philippe Thiran Maria Frucci M. Gabrani 59 69 0 01 Jul 2020
Towards Explainable Graph Representations in Digital Pathology Guillaume Jaume Pushpak Pati A. Foncubierta-Rodríguez Florinda Feroce G. Scognamiglio A. Anniciello Jean-Philippe Thiran O. Goksel M. Gabrani 67 40 0 01 Jul 2020
Visualization for Histopathology Images using Graph Convolutional Neural Networks M. Sureka Abhijeet Patil Deepak Anand A. Sethi FAtt GNN MedIm 45 36 0 16 Jun 2020
Data Efficient and Weakly Supervised Computational Pathology on Whole Slide Images Ming Y. Lu Drew F. K. Williamson Tiffany Y. Chen Richard J. Chen Matteo Barbieri Faisal Mahmood 86 1,308 0 20 Apr 2020
Representation Learning of Histopathology Images using Graph Neural Networks Mohammed Adnan Shivam Kalra Hamid R. Tizhoosh OOD 39 99 0 16 Apr 2020
Pathomic Fusion: An Integrated Framework for Fusing Histopathology and Genomic Features for Cancer Diagnosis and Prognosis Richard J. Chen Ming Y. Lu Jingwen Wang Drew F. K. Williamson S. Rodig N. Lindeman Faisal Mahmood 65 407 0 18 Dec 2019
PyTorch: An Imperative Style, High-Performance Deep Learning Library Adam Paszke Sam Gross Francisco Massa Adam Lerer James Bradbury ... Sasank Chilamkurthy Benoit Steiner Lu Fang Junjie Bai Soumith Chintala ODL 342 42,299 0 03 Dec 2019
Explainable Artificial Intelligence (XAI): Concepts, Taxonomies, Opportunities and Challenges toward Responsible AI Alejandro Barredo Arrieta Natalia Díaz Rodríguez Javier Del Ser Adrien Bennetot Siham Tabik ... S. Gil-Lopez Daniel Molina Richard Benjamins Raja Chatila Francisco Herrera XAI 113 6,235 0 22 Oct 2019
Layerwise Relevance Visualization in Convolutional Text Graph Classifiers Robert Schwarzenberg Marc Hübner David Harbecke Christoph Alt Leonhard Hennig FAtt GNN 43 70 0 24 Sep 2019
Deep Graph Library: A Graph-Centric, Highly-Performant Package for Graph Neural Networks Minjie Wang Da Zheng Zihao Ye Quan Gan Mufei Li ... Jiaqi Zhao Haotong Zhang Alex Smola Jinyang Li Zheng Zhang AI4CE GNN 259 753 0 03 Sep 2019
CGC-Net: Cell Graph Convolutional Network for Grading of Colorectal Cancer Histology Images Yanning Zhou S. Graham Navid Alemi Koohbanani Muhammad Shaban Pheng-Ann Heng Nasir M. Rajpoot MedIm 68 173 0 03 Sep 2019
Resolving challenges in deep learning-based analyses of histopathological images using explanation methods Miriam Hagele P. Seegerer Sebastian Lapuschkin M. Bockmayr Wojciech Samek Frederick Klauschen K. Müller Alexander Binder 89 161 0 15 Aug 2019
Histographs: Graphs in Histopathology Shrey Gadiya Deepak Anand A. Sethi GNN 46 70 0 14 Aug 2019
Explainability Techniques for Graph Convolutional Networks Federico Baldassarre Hossein Azizpour GNN FAtt 158 268 0 31 May 2019
GNNExplainer: Generating Explanations for Graph Neural Networks Rex Ying Dylan Bourgeois Jiaxuan You Marinka Zitnik J. Leskovec LLMAG 125 1,314 0 10 Mar 2019
HoVer-Net: Simultaneous Segmentation and Classification of Nuclei in Multi-Tissue Histology Images S. Graham Q. Vu S. Raza A. Azam Yee Wah Tsang J. T. Kwak Nasir M. Rajpoot 70 1,022 0 16 Dec 2018
Metrics for Explainable AI: Challenges and Prospects R. Hoffman Shane T. Mueller Gary Klein Jordan Litman XAI 72 725 0 11 Dec 2018
How Powerful are Graph Neural Networks? Keyulu Xu Weihua Hu J. Leskovec Stefanie Jegelka GNN 208 7,623 0 01 Oct 2018
Hierarchical Graph Representation Learning with Differentiable Pooling Rex Ying Jiaxuan You Christopher Morris Xiang Ren William L. Hamilton J. Leskovec GNN 256 2,140 0 22 Jun 2018
Towards computational fluorescence microscopy: Machine learning-based integrated prediction of morphological and molecular tumor profiles Alexander Binder M. Bockmayr Miriam Hagele S. Wienert Daniel Heim ... M. Dietel A. Hocke C. Denkert K. Müller Frederick Klauschen AI4CE 51 27 0 28 May 2018
Towards the Augmented Pathologist: Challenges of Explainable-AI in Digital Pathology Andreas Holzinger Bernd Malle Peter Kieseberg P. Roth Heimo Muller Robert Reihs K. Zatloukal 39 91 0 18 Dec 2017
Interpretability Beyond Feature Attribution: Quantitative Testing with Concept Activation Vectors (TCAV) Been Kim Martin Wattenberg Justin Gilmer Carrie J. Cai James Wexler F. Viégas Rory Sayres FAtt 185 1,834 0 30 Nov 2017
Grad-CAM++: Improved Visual Explanations for Deep Convolutional Networks Aditya Chattopadhyay Anirban Sarkar Prantik Howlader V. Balasubramanian FAtt 101 2,285 0 30 Oct 2017
Graph Attention Networks Petar Velickovic Guillem Cucurull Arantxa Casanova Adriana Romero Pietro Lio Yoshua Bengio GNN 416 20,061 0 30 Oct 2017
A Formal Framework to Characterize Interpretability of Procedures Amit Dhurandhar Vijay Iyengar Ronny Luss Karthikeyan Shanmugam 29 19 0 12 Jul 2017
Inductive Representation Learning on Large Graphs William L. Hamilton Z. Ying J. Leskovec 442 15,179 0 07 Jun 2017
Neural Message Passing for Quantum Chemistry Justin Gilmer S. Schoenholz Patrick F. Riley Oriol Vinyals George E. Dahl 415 7,431 0 04 Apr 2017
Towards A Rigorous Science of Interpretable Machine Learning Finale Doshi-Velez Been Kim XAI FaML 366 3,776 0 28 Feb 2017
Visualizing Deep Neural Network Decisions: Prediction Difference Analysis L. Zintgraf Taco S. Cohen T. Adel Max Welling FAtt 129 707 0 15 Feb 2017
Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localization Ramprasaath R. Selvaraju Michael Cogswell Abhishek Das Ramakrishna Vedantam Devi Parikh Dhruv Batra FAtt 246 19,929 0 07 Oct 2016
Semi-Supervised Classification with Graph Convolutional Networks Thomas Kipf Max Welling GNN SSL 559 28,964 0 09 Sep 2016
Convolutional Neural Networks on Graphs with Fast Localized Spectral Filtering M. Defferrard Xavier Bresson P. Vandergheynst GNN 302 7,646 0 30 Jun 2016
Learning Deep Features for Discriminative Localization Bolei Zhou A. Khosla Àgata Lapedriza A. Oliva Antonio Torralba SSL SSeg FAtt 221 9,298 0 14 Dec 2015
Deep Residual Learning for Image Recognition Kaiming He Xinming Zhang Shaoqing Ren Jian Sun MedIm 1.8K 193,426 0 10 Dec 2015
Explaining NonLinear Classification Decisions with Deep Taylor Decomposition G. Montavon Sebastian Lapuschkin Alexander Binder Wojciech Samek Klaus-Robert Muller FAtt 60 733 0 08 Dec 2015
Evaluating the visualization of what a Deep Neural Network has learned Wojciech Samek Alexander Binder G. Montavon Sebastian Lapuschkin K. Müller XAI 124 1,191 0 21 Sep 2015
Understanding Neural Networks Through Deep Visualization J. Yosinski Jeff Clune Anh Totti Nguyen Thomas J. Fuchs Hod Lipson FAtt AI4CE 122 1,871 0 22 Jun 2015
Distilling the Knowledge in a Neural Network Geoffrey E. Hinton Oriol Vinyals J. Dean FedML 300 19,580 0 09 Mar 2015
Adam: A Method for Stochastic Optimization Diederik P. Kingma Jimmy Ba ODL 1.3K 149,842 0 22 Dec 2014
Deep Inside Convolutional Networks: Visualising Image Classification Models and Saliency Maps Karen Simonyan Andrea Vedaldi Andrew Zisserman FAtt 255 7,279 0 20 Dec 2013
Visualizing and Understanding Convolutional Networks Matthew D. Zeiler Rob Fergus FAtt SSL 443 15,861 0 12 Nov 2013