"Why Should I Trust You?": Explaining the Predictions of Any Classifier

"Why Should I Trust You?": Explaining the Predictions of Any Classifier

16 February 2016

Marco Tulio Ribeiro

Carlos Guestrin

Papers citing ""Why Should I Trust You?": Explaining the Predictions of Any Classifier"

16 / 4,266 papers shown

Title
Interpretation of Prediction Models Using the Input Gradient Yotam Hechtlinger FaML AI4CE FAtt 16 85 0 23 Nov 2016
Programs as Black-Box Explanations Sameer Singh Marco Tulio Ribeiro Carlos Guestrin FAtt 24 54 0 22 Nov 2016
An unexpected unity among methods for interpreting model predictions Scott M. Lundberg Su-In Lee FAtt 16 109 0 22 Nov 2016
"Influence Sketching": Finding Influential Samples In Large-Scale Regressions M. Wojnowicz Ben Cruz Xuan Zhao Brian Wallace Matt Wolff Jay Luan Caleb Crable TDI 19 29 0 17 Nov 2016
Nothing Else Matters: Model-Agnostic Explanations By Identifying Prediction Invariance Marco Tulio Ribeiro Sameer Singh Carlos Guestrin FAtt 17 63 0 17 Nov 2016
Low-rank Bilinear Pooling for Fine-Grained Classification Shu Kong Charless C. Fowlkes 33 344 0 16 Nov 2016
Link Prediction using Embedded Knowledge Graphs Yelong Shen Po-Sen Huang Ming-Wei Chang Jianfeng Gao 27 26 0 14 Nov 2016
Safety Verification of Deep Neural Networks Xiaowei Huang Marta Kwiatkowska Sen Wang Min Wu AAML 183 933 0 21 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 68 19,607 0 07 Oct 2016
Correct classification for big/smart/fast data machine learning S. Stepanov 13 0 0 27 Sep 2016
A deep learning model for estimating story points Morakot Choetkiertikul Hoa Dam T. Tran Trang Pham A. Ghose Tim Menzies 24 170 0 02 Sep 2016
Towards Transparent AI Systems: Interpreting Visual Question Answering Models Yash Goyal Akrit Mohapatra Devi Parikh Dhruv Batra 25 74 0 31 Aug 2016
Making Tree Ensembles Interpretable: A Bayesian Model Selection Approach Satoshi Hara K. Hayashi 12 91 0 29 Jun 2016
Increasing the Interpretability of Recurrent Neural Networks Using Hidden Markov Models Viktoriya Krakovna Finale Doshi-Velez AI4CE 37 69 0 16 Jun 2016
Rationalizing Neural Predictions Tao Lei Regina Barzilay Tommi Jaakkola 56 805 0 13 Jun 2016
Auditing Black-box Models for Indirect Influence Philip Adler Casey Falk Sorelle A. Friedler Gabriel Rybeck C. Scheidegger Brandon Smith Suresh Venkatasubramanian TDI MLAU 12 287 0 23 Feb 2016