xGEMs: Generating Examplars to Explain Black-Box Models

22 June 2018

Papers citing "xGEMs: Generating Examplars to Explain Black-Box Models"

29 / 29 papers shown

Title
Identifying Spurious Correlations using Counterfactual Alignment Joseph Paul Cohen Louis Blankemeier Akshay S. Chaudhari CML 84 1 0 01 Dec 2023
Decision-Making with Auto-Encoding Variational Bayes Romain Lopez Pierre Boyeau Nir Yosef Michael I. Jordan Jeffrey Regier BDL 380 10,591 0 17 Feb 2020
Local Explanation Methods for Deep Neural Networks Lack Sensitivity to Parameter Values Julius Adebayo Justin Gilmer Ian Goodfellow Been Kim FAtt AAML 49 128 0 08 Oct 2018
ConvNets and ImageNet Beyond Accuracy: Understanding Mistakes and Uncovering Biases Pierre Stock Moustapha Cissé FaML 66 46 0 30 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 93 685 0 02 Nov 2017
Explanation in Artificial Intelligence: Insights from the Social Sciences Tim Miller XAI 239 4,259 0 22 Jun 2017
On Calibration of Modern Neural Networks Chuan Guo Geoff Pleiss Yu Sun Kilian Q. Weinberger UQCV 291 5,825 0 14 Jun 2017
SmoothGrad: removing noise by adding noise D. Smilkov Nikhil Thorat Been Kim F. Viégas Martin Wattenberg FAtt ODL 201 2,221 0 12 Jun 2017
Understanding Black-box Predictions via Influence Functions Pang Wei Koh Percy Liang TDI 187 2,882 0 14 Mar 2017
Streaming Weak Submodularity: Interpreting Neural Networks on the Fly Ethan R. Elenberg A. Dimakis Moran Feldman Amin Karbasi 42 89 0 08 Mar 2017
Axiomatic Attribution for Deep Networks Mukund Sundararajan Ankur Taly Qiqi Yan OOD FAtt 177 5,986 0 04 Mar 2017
Towards A Rigorous Science of Interpretable Machine Learning Finale Doshi-Velez Been Kim XAI FaML 388 3,785 0 28 Feb 2017
Supervised topic models for clinical interpretability M. C. Hughes Huseyin Melih Elibol T. McCoy R. Perlis Finale Doshi-Velez 43 9 0 06 Dec 2016
Equality of Opportunity in Supervised Learning Moritz Hardt Eric Price Nathan Srebro FaML 220 4,305 0 07 Oct 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 282 19,981 0 07 Oct 2016
Man is to Computer Programmer as Woman is to Homemaker? Debiasing Word Embeddings Tolga Bolukbasi Kai-Wei Chang James Zou Venkatesh Saligrama Adam Kalai CVBM FaML 103 3,133 0 21 Jul 2016
Tutorial on Variational Autoencoders Carl Doersch BDL DRL 96 1,743 0 19 Jun 2016
Early Visual Concept Learning with Unsupervised Deep Learning I. Higgins Loic Matthey Xavier Glorot Arka Pal Benigno Uria Charles Blundell S. Mohamed Alexander Lerchner CoGe OCL DRL 61 173 0 17 Jun 2016
The Mythos of Model Interpretability Zachary Chase Lipton FaML 178 3,690 0 10 Jun 2016
Adversarially Learned Inference Vincent Dumoulin Ishmael Belghazi Ben Poole Olivier Mastropietro Alex Lamb Martín Arjovsky Aaron Courville GAN 72 1,314 0 02 Jun 2016
Asynchrony begets Momentum, with an Application to Deep Learning Jeff Donahue Philipp Krahenbuhl Stefan Hadjis Christopher Ré 92 141 0 31 May 2016
Not Just a Black Box: Learning Important Features Through Propagating Activation Differences Avanti Shrikumar Peyton Greenside A. Shcherbina A. Kundaje FAtt 80 788 0 05 May 2016
"Why Should I Trust You?": Explaining the Predictions of Any Classifier Marco Tulio Ribeiro Sameer Singh Carlos Guestrin FAtt FaML 1.2K 16,954 0 16 Feb 2016
Deep Residual Learning for Image Recognition Kaiming He Xinming Zhang Shaoqing Ren Jian Sun MedIm 2.2K 193,814 0 10 Dec 2015
Visualizing and Understanding Recurrent Networks A. Karpathy Justin Johnson Li Fei-Fei HAI 116 1,101 0 05 Jun 2015
Visualizing and Understanding Neural Models in NLP Jiwei Li Xinlei Chen Eduard H. Hovy Dan Jurafsky MILM FAtt 75 706 0 02 Jun 2015
Monotonic Calibrated Interpolated Look-Up Tables Maya R. Gupta Andrew Cotter Jan Pfeifer Konstantin Voevodski K. Canini Alexander Mangylov Wojtek Moczydlowski A. V. Esbroeck 189 128 0 23 May 2015
Deep Learning Face Attributes in the Wild Ziwei Liu Ping Luo Xiaogang Wang Xiaoou Tang CVBM 239 8,401 0 28 Nov 2014
Deep Inside Convolutional Networks: Visualising Image Classification Models and Saliency Maps Karen Simonyan Andrea Vedaldi Andrew Zisserman FAtt 307 7,289 0 20 Dec 2013