Evaluating the visualization of what a Deep Neural Network has learned

21 September 2015

Papers citing "Evaluating the visualization of what a Deep Neural Network has learned"

50 / 511 papers shown

Title
iNNvestigate neural networks! Maximilian Alber Sebastian Lapuschkin P. Seegerer Miriam Hagele Kristof T. Schütt G. Montavon Wojciech Samek K. Müller Sven Dähne Pieter-Jan Kindermans 13 348 0 13 Aug 2018
Out of the Black Box: Properties of deep neural networks and their applications Nizar Ouarti D. Carmona FAtt AAML 6 3 0 10 Aug 2018
Regional Multi-scale Approach for Visually Pleasing Explanations of Deep Neural Networks Dasom Seo Kanghan Oh Il-Seok Oh FAtt 22 23 0 31 Jul 2018
Layer-wise Relevance Propagation for Explainable Recommendations Homanga Bharadhwaj FAtt 14 8 0 17 Jul 2018
AudioMNIST: Exploring Explainable Artificial Intelligence for Audio Analysis on a Simple Benchmark Sören Becker Johanna Vielhaben M. Ackermann Klaus-Robert Muller Sebastian Lapuschkin Wojciech Samek XAI 24 94 0 09 Jul 2018
A Benchmark for Interpretability Methods in Deep Neural Networks Sara Hooker D. Erhan Pieter-Jan Kindermans Been Kim FAtt UQCV 31 670 0 28 Jun 2018
Quantum-chemical insights from interpretable atomistic neural networks Kristof T. Schütt M. Gastegger A. Tkatchenko K. Müller AI4CE 25 31 0 27 Jun 2018
Towards Robust Interpretability with Self-Explaining Neural Networks David Alvarez-Melis Tommi Jaakkola MILM XAI 50 933 0 20 Jun 2018
Biased Embeddings from Wild Data: Measuring, Understanding and Removing Adam Sutton Thomas Lansdall-Welfare N. Cristianini 18 23 0 16 Jun 2018
Understanding Patch-Based Learning by Explaining Predictions Christopher J. Anders G. Montavon Wojciech Samek K. Müller UQCV FAtt 30 6 0 11 Jun 2018
How Important Is a Neuron? Kedar Dhamdhere Mukund Sundararajan Qiqi Yan FAtt GNN 22 128 0 30 May 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 8 27 0 28 May 2018
VisualBackProp for learning using privileged information with CNNs Devansh Bisla A. Choromańska 12 2 0 24 May 2018
A Theoretical Explanation for Perplexing Behaviors of Backpropagation-based Visualizations Weili Nie Yang Zhang Ankit B. Patel FAtt 13 151 0 18 May 2018
Towards Explaining Anomalies: A Deep Taylor Decomposition of One-Class Models Jacob R. Kauffmann K. Müller G. Montavon DRL 42 96 0 16 May 2018
Detecting Linguistic Characteristics of Alzheimer's Dementia by Interpreting Neural Models Sweta Karlekar Tong Niu Joey Tianyi Zhou 10 107 0 17 Apr 2018
Understanding Autoencoders with Information Theoretic Concepts Shujian Yu José C. Príncipe AI4CE 49 132 0 30 Mar 2018
Visualizing Convolutional Neural Network Protein-Ligand Scoring Joshua E. Hochuli Alec Helbling Tamar Skaist Matthew Ragoza D. Koes FAtt 16 65 0 06 Mar 2018
Improved Explainability of Capsule Networks: Relevance Path by Agreement Atefeh Shahroudnejad Arash Mohammadi Konstantinos N. Plataniotis AAML MedIm 6 62 0 27 Feb 2018
Do WaveNets Dream of Acoustic Waves? Kanru Hua 24 1 0 23 Feb 2018
Explanations based on the Missing: Towards Contrastive Explanations with Pertinent Negatives Amit Dhurandhar Pin-Yu Chen Ronny Luss Chun-Chen Tu Pai-Shun Ting Karthikeyan Shanmugam Payel Das FAtt 15 585 0 21 Feb 2018
Influence-Directed Explanations for Deep Convolutional Networks Klas Leino S. Sen Anupam Datta Matt Fredrikson Linyi Li TDI FAtt 25 75 0 11 Feb 2018
A Survey Of Methods For Explaining Black Box Models Riccardo Guidotti A. Monreale Salvatore Ruggieri Franco Turini D. Pedreschi F. Giannotti XAI 22 3,903 0 06 Feb 2018
Ít's Reducing a Human Being to a Percentage'; Perceptions of Justice in Algorithmic Decisions Reuben Binns Max Van Kleek Michael Veale Ulrik Lyngs Jun Zhao N. Shadbolt FaML 10 514 0 31 Jan 2018
Deep Reinforcement Learning using Capsules in Advanced Game Environments Per-Arne Andersen 18 16 0 29 Jan 2018
Weakly Supervised Object Detection with Pointwise Mutual Information René Grzeszick Sebastian Sudholt G. Fink WSOD 30 1 0 26 Jan 2018
Visual Analytics in Deep Learning: An Interrogative Survey for the Next Frontiers Fred Hohman Minsuk Kahng Robert S. Pienta Duen Horng Chau OOD HAI 41 536 0 21 Jan 2018
Evaluating neural network explanation methods using hybrid documents and morphological agreement Nina Pörner Benjamin Roth Hinrich Schütze 6 9 0 19 Jan 2018
A trans-disciplinary review of deep learning research for water resources scientists Chaopeng Shen AI4CE 33 682 0 06 Dec 2017
Towards better understanding of gradient-based attribution methods for Deep Neural Networks Marco Ancona Enea Ceolini Cengiz Öztireli Markus Gross FAtt 27 145 0 16 Nov 2017
The (Un)reliability of saliency methods Pieter-Jan Kindermans Sara Hooker Julius Adebayo Maximilian Alber Kristof T. Schütt Sven Dähne D. Erhan Been Kim FAtt XAI 42 678 0 02 Nov 2017
Learning Functional Causal Models with Generative Neural Networks Hugo Jair Escalante Sergio Escalera Xavier Baro Isabelle M Guyon Umut Güçlü Marcel van Gerven CML BDL 20 107 0 15 Sep 2017
Machine learning methods for histopathological image analysis D. Komura S. Ishikawa 11 693 0 04 Sep 2017
Explainable Artificial Intelligence: Understanding, Visualizing and Interpreting Deep Learning Models Wojciech Samek Thomas Wiegand K. Müller XAI VLM 34 1,172 0 28 Aug 2017
Understanding and Comparing Deep Neural Networks for Age and Gender Classification Sebastian Lapuschkin Alexander Binder K. Müller Wojciech Samek CVBM 21 135 0 25 Aug 2017
Towards Visual Explanations for Convolutional Neural Networks via Input Resampling Benjamin J. Lengerich Sandeep Konam Eric P. Xing Stephanie Rosenthal Manuela Veloso FAtt XAI 18 5 0 30 Jul 2017
Weakly-supervised localization of diabetic retinopathy lesions in retinal fundus images Waleed M. Gondal Jan M. Köhler René Grzeszick G. Fink M. Hirsch MedIm 24 138 0 29 Jun 2017
Between Homomorphic Signal Processing and Deep Neural Networks: Constructing Deep Algorithms for Polyphonic Music Transcription Li Su 10 21 0 26 Jun 2017
Methods for Interpreting and Understanding Deep Neural Networks G. Montavon Wojciech Samek K. Müller FaML 234 2,238 0 24 Jun 2017
Explaining Recurrent Neural Network Predictions in Sentiment Analysis L. Arras G. Montavon K. Müller Wojciech Samek FAtt 14 352 0 22 Jun 2017
Learning how to explain neural networks: PatternNet and PatternAttribution Pieter-Jan Kindermans Kristof T. Schütt Maximilian Alber K. Müller D. Erhan Been Kim Sven Dähne XAI FAtt 21 338 0 16 May 2017
Clothing and People - A Social Signal Processing Perspective Maedeh Aghaei Federico Parezzan Mariella Dimiccoli P. Radeva Marco Cristani 11 9 0 07 Apr 2017
Axiomatic Attribution for Deep Networks Mukund Sundararajan Ankur Taly Qiqi Yan OOD FAtt 21 5,847 0 04 Mar 2017
"What is Relevant in a Text Document?": An Interpretable Machine Learning Approach L. Arras F. Horn G. Montavon K. Müller Wojciech Samek 17 288 0 23 Dec 2016
Interpreting the Predictions of Complex ML Models by Layer-wise Relevance Propagation Wojciech Samek G. Montavon Alexander Binder Sebastian Lapuschkin K. Müller FAtt AI4CE 24 48 0 24 Nov 2016
Feature Importance Measure for Non-linear Learning Algorithms M. M. Vidovic Nico Görnitz K. Müller Marius Kloft FAtt 16 39 0 22 Nov 2016
VisualBackProp: efficient visualization of CNNs Mariusz Bojarski A. Choromańska K. Choromanski Bernhard Firner L. Jackel Urs Muller Karol Zieba FAtt 28 74 0 16 Nov 2016
Gradients of Counterfactuals Mukund Sundararajan Ankur Taly Qiqi Yan FAtt 13 105 0 08 Nov 2016
Deep image mining for diabetic retinopathy screening G. Quellec K. Charrière Yassine Boudi B. Cochener M. Lamard MedIm 36 413 0 22 Oct 2016
Interpreting Neural Networks to Improve Politeness Comprehension Malika Aubakirova Joey Tianyi Zhou FAtt MILM 11 56 0 09 Oct 2016