Twin Systems for DeepCBR: A Menagerie of Deep Learning and Case-Based Reasoning Pairings for Explanation and Data Augmentation

29 April 2021

Papers citing "Twin Systems for DeepCBR: A Menagerie of Deep Learning and Case-Based Reasoning Pairings for Explanation and Data Augmentation"

9 / 9 papers shown

Title
On Generating Plausible Counterfactual and Semi-Factual Explanations for Deep Learning Eoin M. Kenny Mark T. Keane 54 100 0 10 Sep 2020
The Dangers of Post-hoc Interpretability: Unjustified Counterfactual Explanations Thibault Laugel Marie-Jeanne Lesot Christophe Marsala X. Renard Marcin Detyniecki 48 197 0 22 Jul 2019
Medical Image Synthesis for Data Augmentation and Anonymization using Generative Adversarial Networks Hoo-Chang Shin Neil A. Tenenholtz Jameson K. Rogers C. Schwarz M. Senjem J. Gunter Katherine P. Andriole Mark H. Michalski MedIm 96 540 0 26 Jul 2018
Deep k-Nearest Neighbors: Towards Confident, Interpretable and Robust Deep Learning Nicolas Papernot Patrick McDaniel OOD AAML 127 507 0 13 Mar 2018
Data Augmentation Generative Adversarial Networks Antreas Antoniou Amos Storkey Harrison Edwards MedIm GAN 129 1,070 0 12 Nov 2017
Counterfactual Explanations without Opening the Black Box: Automated Decisions and the GDPR Sandra Wachter Brent Mittelstadt Chris Russell MLAU 98 2,348 0 01 Nov 2017
Explanation in Artificial Intelligence: Insights from the Social Sciences Tim Miller XAI 236 4,249 0 22 Jun 2017
The Mythos of Model Interpretability Zachary Chase Lipton FaML 154 3,685 0 10 Jun 2016
Learning Deep Features for Discriminative Localization Bolei Zhou A. Khosla Àgata Lapedriza A. Oliva Antonio Torralba SSL SSeg FAtt 223 9,298 0 14 Dec 2015