v1v2 (latest)

Distilling Model Failures as Directions in Latent Space

29 June 2022

ArXiv (abs)PDF HTML Github (47★)

Papers citing "Distilling Model Failures as Directions in Latent Space"

22 / 72 papers shown

Title
Multiaccuracy: Black-Box Post-Processing for Fairness in Classification Michael P. Kim Amirata Ghorbani James Zou MLAU 248 345 0 31 May 2018
Datasheets for Datasets Timnit Gebru Jamie Morgenstern Briana Vecchione Jennifer Wortman Vaughan Hanna M. Wallach Hal Daumé Kate Crawford 292 2,201 0 23 Mar 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 129 592 0 21 Feb 2018
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 242 1,849 0 30 Nov 2017
CheXNet: Radiologist-Level Pneumonia Detection on Chest X-Rays with Deep Learning Pranav Rajpurkar Jeremy Irvin Kaylie Zhu Brandon Yang Hershel Mehta ... Aarti Bagul C. Langlotz K. Shpanskaya M. Lungren A. Ng LM&MA 99 2,712 0 14 Nov 2017
Towards Deep Learning Models Resistant to Adversarial Attacks Aleksander Madry Aleksandar Makelov Ludwig Schmidt Dimitris Tsipras Adrian Vladu SILM OOD 319 12,151 0 19 Jun 2017
Real Time Image Saliency for Black Box Classifiers P. Dabkowski Y. Gal 72 593 0 22 May 2017
Network Dissection: Quantifying Interpretability of Deep Visual Representations David Bau Bolei Zhou A. Khosla A. Oliva Antonio Torralba MILM FAtt 158 1,526 1 19 Apr 2017
Interpretable Explanations of Black Boxes by Meaningful Perturbation Ruth C. Fong Andrea Vedaldi FAtt AAML 83 1,526 0 11 Apr 2017
Counterfactual Fairness Matt J. Kusner Joshua R. Loftus Chris Russell Ricardo M. A. Silva FaML 228 1,588 0 20 Mar 2017
Understanding Black-box Predictions via Influence Functions Pang Wei Koh Percy Liang TDI 219 2,910 0 14 Mar 2017
Axiomatic Attribution for Deep Networks Mukund Sundararajan Ankur Taly Qiqi Yan OOD FAtt 193 6,027 0 04 Mar 2017
Visualizing Deep Neural Network Decisions: Prediction Difference Analysis L. Zintgraf Taco S. Cohen T. Adel Max Welling FAtt 147 709 0 15 Feb 2017
Fairness Beyond Disparate Treatment & Disparate Impact: Learning Classification without Disparate Mistreatment Muhammad Bilal Zafar Isabel Valera Manuel Gomez Rodriguez Krishna P. Gummadi FaML 208 1,214 0 26 Oct 2016
Equality of Opportunity in Supervised Learning Moritz Hardt Eric Price Nathan Srebro FaML 236 4,341 0 07 Oct 2016
"Why Should I Trust You?": Explaining the Predictions of Any Classifier Marco Tulio Ribeiro Sameer Singh Carlos Guestrin FAtt FaML 1.2K 17,071 0 16 Feb 2016
Rethinking the Inception Architecture for Computer Vision Christian Szegedy Vincent Vanhoucke Sergey Ioffe Jonathon Shlens Z. Wojna 3DV BDL 886 27,427 0 02 Dec 2015
Explaining and Harnessing Adversarial Examples Ian Goodfellow Jonathon Shlens Christian Szegedy AAML GAN 282 19,129 0 20 Dec 2014
Certifying and removing disparate impact Michael Feldman Sorelle A. Friedler John Moeller C. Scheidegger Suresh Venkatasubramanian FaML 208 1,996 0 11 Dec 2014
Deep Learning Face Attributes in the Wild Ziwei Liu Ping Luo Xiaogang Wang Xiaoou Tang CVBM 253 8,429 0 28 Nov 2014
Intriguing properties of neural networks Christian Szegedy Wojciech Zaremba Ilya Sutskever Joan Bruna D. Erhan Ian Goodfellow Rob Fergus AAML 289 14,968 1 21 Dec 2013
Deep Inside Convolutional Networks: Visualising Image Classification Models and Saliency Maps Karen Simonyan Andrea Vedaldi Andrew Zisserman FAtt 317 7,321 0 20 Dec 2013