v1v2v3 (latest)

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

16 February 2016

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

50 / 4,973 papers shown

Title
Efficient computation of counterfactual explanations of LVQ models André Artelt Barbara Hammer 54 16 0 02 Aug 2019
Visualizing RNN States with Predictive Semantic Encodings Lindsey Sawatzky Steven Bergner F. Popowich 47 6 0 01 Aug 2019
A Survey on Deep Learning of Small Sample in Biomedical Image Analysis Pengyi Zhang Yunxin Zhong Yulin Deng Xiaoying Tang Xiaoqiong Li 69 32 0 01 Aug 2019
FairSight: Visual Analytics for Fairness in Decision Making Yongsu Ahn Y. Lin 79 125 0 01 Aug 2019
Machine Learning at the Network Edge: A Survey M. G. Sarwar Murshed Chris Murphy Daqing Hou Nazar Khan Ganesh Ananthanarayanan Faraz Hussain 92 391 0 31 Jul 2019
Adapting SQuaRE for Quality Assessment of Artificial Intelligence Systems Hiroshi Kuwajima Fuyuki Ishikawa 39 34 0 31 Jul 2019
What's in the box? Explaining the black-box model through an evaluation of its interpretable features F. Ventura Tania Cerquitelli 18 2 0 31 Jul 2019
Local Interpretation Methods to Machine Learning Using the Domain of the Feature Space T. Botari Rafael Izbicki A. Carvalho FAtt 42 12 0 31 Jul 2019
Graph Space Embedding J. Pereira A. Groen E. Stroes E. Levin 22 4 0 31 Jul 2019
The Challenge of Imputation in Explainable Artificial Intelligence Models M. Ahmad C. Eckert Ankur Teredesai 23 8 0 29 Jul 2019
LassoNet: A Neural Network with Feature Sparsity Ismael Lemhadri Feng Ruan L. Abraham Robert Tibshirani 146 131 0 29 Jul 2019
How model accuracy and explanation fidelity influence user trust A. Papenmeier G. Englebienne C. Seifert FaML 54 110 0 26 Jul 2019
Personalised novel and explainable matrix factorisation Ludovik Çoba P. Symeonidis Markus Zanker 44 12 0 25 Jul 2019
How to Manipulate CNNs to Make Them Lie: the GradCAM Case T. Viering Ziqi Wang Marco Loog E. Eisemann AAML FAtt 58 28 0 25 Jul 2019
Visual Interaction with Deep Learning Models through Collaborative Semantic Inference Sebastian Gehrmann Hendrik Strobelt Robert Krüger Hanspeter Pfister Alexander M. Rush HAI 101 58 0 24 Jul 2019
Interpretable and Steerable Sequence Learning via Prototypes Yao Ming Panpan Xu Huamin Qu Liu Ren AI4TS 66 141 0 23 Jul 2019
Benchmarking Attribution Methods with Relative Feature Importance Mengjiao Yang Been Kim FAtt XAI 75 142 0 23 Jul 2019
The Dangers of Post-hoc Interpretability: Unjustified Counterfactual Explanations Thibault Laugel Marie-Jeanne Lesot Christophe Marsala X. Renard Marcin Detyniecki 102 197 0 22 Jul 2019
Scalable Topological Data Analysis and Visualization for Evaluating Data-Driven Models in Scientific Applications Shusen Liu Di Wang D. Maljovec Rushil Anirudh Jayaraman J. Thiagarajan ... Peter B. Robinson H. Bhatia Valerio Pascucci B. Spears P. Bremer 15 11 0 19 Jul 2019
Why Does My Model Fail? Contrastive Local Explanations for Retail Forecasting Ana Lucic H. Haned Maarten de Rijke 68 64 0 17 Jul 2019
A Survey on Explainable Artificial Intelligence (XAI): Towards Medical XAI Erico Tjoa Cuntai Guan XAI 158 1,463 0 17 Jul 2019
Evaluating Explanation Without Ground Truth in Interpretable Machine Learning Fan Yang Mengnan Du Helen Zhou XAI ELM 67 67 0 16 Jul 2019
Technical Report: Partial Dependence through Stratification T. Parr James D. Wilson 29 3 0 15 Jul 2019
A study on the Interpretability of Neural Retrieval Models using DeepSHAP Zeon Trevor Fernando Jaspreet Singh Avishek Anand FAtt AAML 65 68 0 15 Jul 2019
Metamorphic Testing of a Deep Learning based Forecaster Anurag Dwarakanath Manish Ahuja Sanjay Podder Silja Vinu Arijit Naskar M. Koushik AI4TS 43 9 0 13 Jul 2019
Saliency Maps Generation for Automatic Text Summarization David Tuckey Krysia Broda A. Russo FAtt 48 3 0 12 Jul 2019
Sparsely Activated Networks Paschalis A. Bizopoulos D. Koutsouris 31 12 0 12 Jul 2019
A Systematic Mapping Study on Testing of Machine Learning Programs S. Sherin Muhammad Uzair Khan Muhammad Zohaib Z. Iqbal 39 13 0 11 Jul 2019
Aerial Animal Biometrics: Individual Friesian Cattle Recovery and Visual Identification via an Autonomous UAV with Onboard Deep Inference William Andrew C. Greatwood T. Burghardt 71 52 0 11 Jul 2019
Forecasting remaining useful life: Interpretable deep learning approach via variational Bayesian inferences Mathias Kraus Stefan Feuerriegel 64 110 0 11 Jul 2019
Explaining an increase in predicted risk for clinical alerts Michaela Hardt A. Rajkomar Gerardo Flores Andrew M. Dai M. Howell Greg S. Corrado Claire Cui Moritz Hardt FAtt 67 12 0 10 Jul 2019
The What-If Tool: Interactive Probing of Machine Learning Models James Wexler Mahima Pushkarna Tolga Bolukbasi Martin Wattenberg F. Viégas Jimbo Wilson VLM 97 499 0 09 Jul 2019
Optimal Explanations of Linear Models Dimitris Bertsimas A. Delarue Patrick Jaillet Sébastien Martin FAtt 38 2 0 08 Jul 2019
The Price of Interpretability Dimitris Bertsimas A. Delarue Patrick Jaillet Sébastien Martin 63 34 0 08 Jul 2019
Case-Based Reasoning for Assisting Domain Experts in Processing Fraud Alerts of Black-Box Machine Learning Models Hilde J. P. Weerts Werner van Ipenburg Mykola Pechenizkiy 35 3 0 07 Jul 2019
A Human-Grounded Evaluation of SHAP for Alert Processing Hilde J. P. Weerts Werner van Ipenburg Mykola Pechenizkiy FAtt 73 70 0 07 Jul 2019
Generative Counterfactual Introspection for Explainable Deep Learning Shusen Liu B. Kailkhura Donald Loveland Yong Han 138 90 0 06 Jul 2019
Global Aggregations of Local Explanations for Black Box models I. V. D. Linden H. Haned Evangelos Kanoulas FAtt 71 66 0 05 Jul 2019
Explaining Predictions from Tree-based Boosting Ensembles Ana Lucic H. Haned Maarten de Rijke FAtt 46 5 0 04 Jul 2019
On Validating, Repairing and Refining Heuristic ML Explanations Alexey Ignatiev Nina Narodytska Sasha Rubin FAtt LRM 76 63 0 04 Jul 2019
Automating Distributed Tiered Storage Management in Cluster Computing H. Herodotou E. Kakoulli 30 25 0 04 Jul 2019
Consistent Regression using Data-Dependent Coverings Vincent Margot Jean-Patrick Baudry Frédéric Guilloux Olivier Wintenberger 36 5 0 04 Jul 2019
Machine learning and behavioral economics for personalized choice architecture Emir Hrnjic N. Tomczak CML AI4CE 56 8 0 03 Jul 2019
Interpretable Counterfactual Explanations Guided by Prototypes A. V. Looveren Janis Klaise FAtt 100 387 0 03 Jul 2019
A Case Study of Deep-Learned Activations via Hand-Crafted Audio Features Olga Slizovskaia E. Gómez G. Haro 19 1 0 03 Jul 2019
Towards Interpretable Deep Extreme Multi-label Learning Yihuang Kang I-Ling Cheng W. Mao Bowen Kuo Pei-Ju Lee 18 0 0 03 Jul 2019
How we do things with words: Analyzing text as social and cultural data D. Nguyen Maria Liakata Simon DeDeo Jacob Eisenstein David M. Mimno Rebekah Tromble J. Winters 65 88 0 02 Jul 2019
On the Privacy Risks of Model Explanations Reza Shokri Martin Strobel Yair Zick MIACV PILM SILM FAtt 126 38 0 29 Jun 2019
A Debiased MDI Feature Importance Measure for Random Forests Xiao Li Yu Wang Sumanta Basu Karl Kumbier Bin Yu 224 86 0 26 Jun 2019
Explaining Deep Learning Models with Constrained Adversarial Examples J. Moore Nils Y. Hammerla C. Watkins AAML GAN 67 38 0 25 Jun 2019