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Explanation by Progressive Exaggeration

1 November 2019

Kayhan Batmanghelich

Papers citing "Explanation by Progressive Exaggeration"

29 / 79 papers shown

Title
Robust Feature-Level Adversaries are Interpretability Tools Stephen Casper Max Nadeau Dylan Hadfield-Menell Gabriel Kreiman AAML 203 28 0 07 Oct 2021
Designing Counterfactual Generators using Deep Model Inversion Jayaraman J. Thiagarajan V. Narayanaswamy Deepta Rajan J. Liang Akshay S. Chaudhari A. Spanias DiffM 62 22 0 29 Sep 2021
Explainability Requires Interactivity Matthias Kirchler M. Graf Marius Kloft C. Lippert FAtt AAML HAI 65 1 0 16 Sep 2021
CounterNet: End-to-End Training of Prediction Aware Counterfactual Explanations Hangzhi Guo T. Nguyen A. Yadav OffRL 68 17 0 15 Sep 2021
VAE-CE: Visual Contrastive Explanation using Disentangled VAEs Y. Poels Vlado Menkovski CoGe DRL 87 3 0 20 Aug 2021
Neural-to-Tree Policy Distillation with Policy Improvement Criterion Zhaorong Li Yang Yu Yingfeng Chen Ke Chen Zhipeng Hu Changjie Fan 45 5 0 16 Aug 2021
Using Causal Analysis for Conceptual Deep Learning Explanation Sumedha Singla Stephen Wallace Sofia Triantafillou Kayhan Batmanghelich CML 58 15 0 10 Jul 2021
Meaningfully Debugging Model Mistakes using Conceptual Counterfactual Explanations Abubakar Abid Mert Yuksekgonul James Zou CML 123 64 0 24 Jun 2021
Leveraging Conditional Generative Models in a General Explanation Framework of Classifier Decisions Martin Charachon P. Cournède C´eline Hudelot R. Ardon 51 5 0 21 Jun 2021
DISSECT: Disentangled Simultaneous Explanations via Concept Traversals Asma Ghandeharioun Been Kim Chun-Liang Li Brendan Jou B. Eoff Rosalind W. Picard AAML 113 54 0 31 May 2021
Two4Two: Evaluating Interpretable Machine Learning - A Synthetic Dataset For Controlled Experiments M. Schuessler Philipp Weiß Leon Sixt 75 3 0 06 May 2021
Explaining in Style: Training a GAN to explain a classifier in StyleSpace Oran Lang Yossi Gandelsman Michal Yarom Yoav Wald G. Elidan ... William T. Freeman Phillip Isola Amir Globerson Michal Irani Inbar Mosseri GAN 130 153 0 27 Apr 2021
Beyond Trivial Counterfactual Explanations with Diverse Valuable Explanations Pau Rodríguez López Massimo Caccia Alexandre Lacoste L. Zamparo I. Laradji Laurent Charlin David Vazquez AAML 109 58 0 18 Mar 2021
If Only We Had Better Counterfactual Explanations: Five Key Deficits to Rectify in the Evaluation of Counterfactual XAI Techniques Mark T. Keane Eoin M. Kenny Eoin Delaney Barry Smyth CML 94 148 0 26 Feb 2021
Gifsplanation via Latent Shift: A Simple Autoencoder Approach to Counterfactual Generation for Chest X-rays Joseph Paul Cohen Rupert Brooks Sovann En Evan Zucker Anuj Pareek M. Lungren Akshay S. Chaudhari FAtt MedIm 97 4 0 18 Feb 2021
Generative Counterfactuals for Neural Networks via Attribute-Informed Perturbation Fan Yang Ninghao Liu Mengnan Du X. Hu OOD 61 17 0 18 Jan 2021
Explainability of deep vision-based autonomous driving systems: Review and challenges Éloi Zablocki H. Ben-younes P. Pérez Matthieu Cord XAI 186 177 0 13 Jan 2021
Explaining the Black-box Smoothly- A Counterfactual Approach Junyu Chen Yong Du Yufan He W. Paul Segars Ye Li MedIm FAtt 152 109 0 11 Jan 2021
Concept-based model explanations for Electronic Health Records Diana Mincu Eric Loreaux Shaobo Hou Sebastien Baur Ivan V. Protsyuk Martin G. Seneviratne A. Mottram Nenad Tomašev Alan Karthikesanlingam Jessica Schrouff 84 28 0 03 Dec 2020
Human-interpretable model explainability on high-dimensional data Damien de Mijolla Christopher Frye M. Kunesch J. Mansir Ilya Feige FAtt 65 10 0 14 Oct 2020
Explaining Clinical Decision Support Systems in Medical Imaging using Cycle-Consistent Activation Maximization Alexander Katzmann O. Taubmann Stephen Ahmad Alexander Muhlberg M. Sühling H. Groß MedIm 43 20 0 09 Oct 2020
Counterfactual Explanation and Causal Inference in Service of Robustness in Robot Control Simón C. Smith S. Ramamoorthy 84 14 0 18 Sep 2020
On Generating Plausible Counterfactual and Semi-Factual Explanations for Deep Learning Eoin M. Kenny Mark T. Keane 79 105 0 10 Sep 2020
DECE: Decision Explorer with Counterfactual Explanations for Machine Learning Models Furui Cheng Yao Ming Huamin Qu CML HAI 54 101 0 19 Aug 2020
Understanding and Diagnosing Vulnerability under Adversarial Attacks Haizhong Zheng Ziqi Zhang Honglak Lee A. Prakash FAtt AAML 76 6 0 17 Jul 2020
Towards causal benchmarking of bias in face analysis algorithms Guha Balakrishnan Yuanjun Xiong Wei Xia Pietro Perona CVBM 82 90 0 13 Jul 2020
Scientific Discovery by Generating Counterfactuals using Image Translation Arunachalam Narayanaswamy Subhashini Venugopalan D. Webster L. Peng G. Corrado ... Abigail E. Huang Siva Balasubramanian Michael P. Brenner Phil Q. Nelson A. Varadarajan DiffM MedIm 134 21 0 10 Jul 2020
COVID-19 Image Data Collection: Prospective Predictions Are the Future Joseph Paul Cohen Paul Morrison Lan Dao Karsten Roth T. Duong Marzyeh Ghassemi 106 781 0 22 Jun 2020
Deep Structural Causal Models for Tractable Counterfactual Inference Nick Pawlowski Daniel Coelho De Castro Ben Glocker CML MedIm 133 245 0 11 Jun 2020