Deep Relevance Regularization: Interpretable and Robust Tumor Typing of
Imaging Mass Spectrometry Data

Deep Relevance Regularization: Interpretable and Robust Tumor Typing of Imaging Mass Spectrometry Data

10 December 2019

Christian Etmann

Maximilian Schmidt

Lena Hauberg-Lotte

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Papers citing "Deep Relevance Regularization: Interpretable and Robust Tumor Typing of Imaging Mass Spectrometry Data"

17 / 17 papers shown

Title
Interpretations are useful: penalizing explanations to align neural networks with prior knowledge Laura Rieger Chandan Singh W. James Murdoch Bin Yu FAtt 96 215 0 30 Sep 2019
A Forward-Backward Approach for Visualizing Information Flow in Deep Networks Aditya Balu THANH VAN NGUYEN Apurva Kokate Chinmay Hegde Soumik Sarkar FAtt 31 9 0 16 Nov 2017
Towards better understanding of gradient-based attribution methods for Deep Neural Networks Marco Ancona Enea Ceolini Cengiz Öztireli Markus Gross FAtt 68 147 0 16 Nov 2017
Methods for Interpreting and Understanding Deep Neural Networks G. Montavon Wojciech Samek K. Müller FaML 293 2,267 0 24 Jun 2017
Deep Learning for Tumor Classification in Imaging Mass Spectrometry Jens Behrmann Christian Etmann T. Boskamp R. Casadonte J. Kriegsmann Peter Maass 76 104 0 02 May 2017
Right for the Right Reasons: Training Differentiable Models by Constraining their Explanations A. Ross M. C. Hughes Finale Doshi-Velez FAtt 133 591 0 10 Mar 2017
Visualizing Deep Neural Network Decisions: Prediction Difference Analysis L. Zintgraf Taco S. Cohen T. Adel Max Welling FAtt 143 708 0 15 Feb 2017
Investigating the influence of noise and distractors on the interpretation of neural networks Pieter-Jan Kindermans Kristof T. Schütt K. Müller Sven Dähne FAtt 74 125 0 22 Nov 2016
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 325 20,110 0 07 Oct 2016
Top-down Neural Attention by Excitation Backprop Jianming Zhang Zhe Lin Jonathan Brandt Xiaohui Shen Stan Sclaroff 92 948 0 01 Aug 2016
Not Just a Black Box: Learning Important Features Through Propagating Activation Differences Avanti Shrikumar Peyton Greenside A. Shcherbina A. Kundaje FAtt 87 791 0 05 May 2016
Deep Residual Learning for Image Recognition Kaiming He Xinming Zhang Shaoqing Ren Jian Sun MedIm 2.2K 194,510 0 10 Dec 2015
Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification Kaiming He Xinming Zhang Shaoqing Ren Jian Sun VLM 344 18,654 0 06 Feb 2015
Adam: A Method for Stochastic Optimization Diederik P. Kingma Jimmy Ba ODL 2.1K 150,364 0 22 Dec 2014
Striving for Simplicity: The All Convolutional Net Jost Tobias Springenberg Alexey Dosovitskiy Thomas Brox Martin Riedmiller FAtt 254 4,681 0 21 Dec 2014
Deep Inside Convolutional Networks: Visualising Image Classification Models and Saliency Maps Karen Simonyan Andrea Vedaldi Andrew Zisserman FAtt 314 7,317 0 20 Dec 2013
Visualizing and Understanding Convolutional Networks Matthew D. Zeiler Rob Fergus FAtt SSL 595 15,904 0 12 Nov 2013