DECE: Decision Explorer with Counterfactual Explanations for Machine Learning Models

19 August 2020

Huamin Qu

Papers citing "DECE: Decision Explorer with Counterfactual Explanations for Machine Learning Models"

27 / 27 papers shown

Title
Distributional Counterfactual Explanations With Optimal Transport Lei You Lele Cao Mattias Nilsson Bo Zhao Lei Lei OT OffRL 128 1 0 23 Jan 2024
PRINCE: Provider-side Interpretability with Counterfactual Explanations in Recommender Systems Azin Ghazimatin Oana Balalau Rishiraj Saha Roy Gerhard Weikum FAtt 82 99 0 19 Nov 2019
Explanation by Progressive Exaggeration Sumedha Singla Brian Pollack Junxiang Chen Kayhan Batmanghelich FAtt MedIm 96 103 0 01 Nov 2019
FairSight: Visual Analytics for Fairness in Decision Making Yongsu Ahn Y. Lin 69 123 0 01 Aug 2019
explAIner: A Visual Analytics Framework for Interactive and Explainable Machine Learning Thilo Spinner U. Schlegel H. Schäfer Mennatallah El-Assady HAI 76 239 0 29 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 81 494 0 09 Jul 2019
Model-Agnostic Counterfactual Explanations for Consequential Decisions Amir-Hossein Karimi Gilles Barthe Borja Balle Isabel Valera 91 324 0 27 May 2019
Explainable Reinforcement Learning Through a Causal Lens Prashan Madumal Tim Miller L. Sonenberg F. Vetere CML 106 361 0 27 May 2019
Explaining Machine Learning Classifiers through Diverse Counterfactual Explanations R. Mothilal Amit Sharma Chenhao Tan CML 128 1,029 0 19 May 2019
Summit: Scaling Deep Learning Interpretability by Visualizing Activation and Attribution Summarizations Fred Hohman Haekyu Park Caleb Robinson Duen Horng Chau FAtt 3DH HAI 55 218 0 04 Apr 2019
Efficient Search for Diverse Coherent Explanations Chris Russell 75 238 0 02 Jan 2019
Synthesizing Tabular Data using Generative Adversarial Networks L. Xu K. Veeramachaneni CML GAN 79 252 0 27 Nov 2018
Actionable Recourse in Linear Classification Berk Ustun Alexander Spangher Yang Liu FaML 129 551 0 18 Sep 2018
Techniques for Interpretable Machine Learning Mengnan Du Ninghao Liu Helen Zhou FaML 93 1,092 0 31 Jul 2018
RuleMatrix: Visualizing and Understanding Classifiers with Rules Yao Ming Huamin Qu E. Bertini FAtt 67 215 0 17 Jul 2018
Seq2Seq-Vis: A Visual Debugging Tool for Sequence-to-Sequence Models Hendrik Strobelt Sebastian Gehrmann M. Behrisch Adam Perer Hanspeter Pfister Alexander M. Rush VLM HAI 56 240 0 25 Apr 2018
Ít's Reducing a Human Being to a Percentage'; Perceptions of Justice in Algorithmic Decisions Reuben Binns Max Van Kleek Michael Veale Ulrik Lyngs Jun Zhao N. Shadbolt FaML 69 546 0 31 Jan 2018
Visual Analytics in Deep Learning: An Interrogative Survey for the Next Frontiers Fred Hohman Minsuk Kahng Robert S. Pienta Duen Horng Chau OOD HAI 84 541 0 21 Jan 2018
Counterfactual Explanations without Opening the Black Box: Automated Decisions and the GDPR Sandra Wachter Brent Mittelstadt Chris Russell MLAU 135 2,366 0 01 Nov 2017
Understanding Hidden Memories of Recurrent Neural Networks Yao Ming Shaozu Cao Ruixiang Zhang Zerui Li Yuanzhe Chen Yangqiu Song Huamin Qu HAI 40 201 0 30 Oct 2017
Do Convolutional Neural Networks Learn Class Hierarchy? B. Alsallakh Amin Jourabloo Mao Ye Xiaoming Liu Liu Ren 178 214 0 17 Oct 2017
Explanation in Artificial Intelligence: Insights from the Social Sciences Tim Miller XAI 252 4,281 0 22 Jun 2017
A Workflow for Visual Diagnostics of Binary Classifiers using Instance-Level Explanations Josua Krause Aritra Dasgupta Jordan Swartz Yindalon Aphinyanagphongs E. Bertini FAtt 58 96 0 04 May 2017
ActiVis: Visual Exploration of Industry-Scale Deep Neural Network Models Minsuk Kahng Pierre Yves Andrews Aditya Kalro Duen Horng Chau HAI 75 324 0 06 Apr 2017
Towards Better Analysis of Machine Learning Models: A Visual Analytics Perspective Shixia Liu Xiting Wang Mengchen Liu Jun Zhu HAI 51 365 0 04 Feb 2017
Towards Better Analysis of Deep Convolutional Neural Networks Mengchen Liu Jiaxin Shi Zerui Li Chongxuan Li Jun Zhu Shixia Liu HAI 105 477 0 24 Apr 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