Towards A Rigorous Science of Interpretable Machine Learning

28 February 2017

Finale Doshi-Velez

Papers citing "Towards A Rigorous Science of Interpretable Machine Learning"

50 / 404 papers shown

Title
Attribution-based XAI Methods in Computer Vision: A Review Kumar Abhishek Deeksha Kamath 27 18 0 27 Nov 2022
MEGAN: Multi-Explanation Graph Attention Network Jonas Teufel Luca Torresi Patrick Reiser Pascal Friederich 16 8 0 23 Nov 2022
Concept-based Explanations using Non-negative Concept Activation Vectors and Decision Tree for CNN Models Gayda Mutahar Tim Miller FAtt 24 6 0 19 Nov 2022
CRAFT: Concept Recursive Activation FacTorization for Explainability Thomas Fel Agustin Picard Louis Bethune Thibaut Boissin David Vigouroux Julien Colin Rémi Cadène Thomas Serre 19 102 0 17 Nov 2022
Explainable Artificial Intelligence: Precepts, Methods, and Opportunities for Research in Construction Peter E. D. Love Weili Fang J. Matthews Stuart Porter Hanbin Luo L. Ding XAI 29 7 0 12 Nov 2022
On the Robustness of Explanations of Deep Neural Network Models: A Survey Amlan Jyoti Karthik Balaji Ganesh Manoj Gayala Nandita Lakshmi Tunuguntla Sandesh Kamath V. Balasubramanian XAI FAtt AAML 32 4 0 09 Nov 2022
$Individualized and Global Feature Attributions for Gradient Boosted Trees in the Presence of $\ell_2$ Regularization$ Individualized and Global Feature Attributions for Gradient Boosted Trees in the Presence of $\ell_2$ Regularization Qingyao Sun 26 2 0 08 Nov 2022
ViT-CX: Causal Explanation of Vision Transformers Weiyan Xie Xiao-hui Li Caleb Chen Cao Nevin L.Zhang ViT 24 17 0 06 Nov 2022
Towards Human Cognition Level-based Experiment Design for Counterfactual Explanations (XAI) M. Nizami Muhammad Yaseen Khan Alessandro Bogliolo 11 3 0 31 Oct 2022
Generating Hierarchical Explanations on Text Classification Without Connecting Rules Yiming Ju Yuanzhe Zhang Kang Liu Jun Zhao FAtt 18 3 0 24 Oct 2022
Towards Procedural Fairness: Uncovering Biases in How a Toxic Language Classifier Uses Sentiment Information I. Nejadgholi Esma Balkir Kathleen C. Fraser S. Kiritchenko 32 3 0 19 Oct 2022
Towards Explaining Distribution Shifts Sean Kulinski David I. Inouye OffRL FAtt 35 23 0 19 Oct 2022
Machine Learning in Transaction Monitoring: The Prospect of xAI Julie Gerlings Ioanna D. Constantiou 17 2 0 14 Oct 2022
On the Explainability of Natural Language Processing Deep Models Julia El Zini M. Awad 25 82 0 13 Oct 2022
Neurosymbolic Programming for Science Jennifer J. Sun Megan Tjandrasuwita Atharva Sehgal Armando Solar-Lezama Swarat Chaudhuri Yisong Yue Omar Costilla-Reyes NAI 35 12 0 10 Oct 2022
Using Knowledge Distillation to improve interpretable models in a retail banking context Maxime Biehler Mohamed Guermazi Célim Starck 49 2 0 30 Sep 2022
Empowering the trustworthiness of ML-based critical systems through engineering activities J. Mattioli Agnès Delaborde Souhaiel Khalfaoui Freddy Lecue H. Sohier F. Jurie 9 2 0 30 Sep 2022
Counterfactual Explanations Using Optimization With Constraint Learning Donato Maragno Tabea E. Rober Ilker Birbil CML 47 10 0 22 Sep 2022
XClusters: Explainability-first Clustering Hyunseung Hwang Steven Euijong Whang 21 5 0 22 Sep 2022
Summarization Programs: Interpretable Abstractive Summarization with Neural Modular Trees Swarnadeep Saha Shiyue Zhang Peter Hase Mohit Bansal 26 19 0 21 Sep 2022
The Ability of Image-Language Explainable Models to Resemble Domain Expertise P. Werner Anna Zapaishchykova Ujjwal Ratan 40 2 0 19 Sep 2022
MSVIPER: Improved Policy Distillation for Reinforcement-Learning-Based Robot Navigation Aaron M. Roth Jing Liang Ram D. Sriram Elham Tabassi Dinesh Manocha 24 1 0 19 Sep 2022
Explainable AI for clinical and remote health applications: a survey on tabular and time series data Flavio Di Martino Franca Delmastro AI4TS 23 91 0 14 Sep 2022
Lost in Translation: Reimagining the Machine Learning Life Cycle in Education Lydia T. Liu Serena Wang Tolani A. Britton Rediet Abebe AI4Ed 19 1 0 08 Sep 2022
Making the black-box brighter: interpreting machine learning algorithm for forecasting drilling accidents E. Gurina Nikita Klyuchnikov Ksenia Antipova D. Koroteev FAtt 25 8 0 06 Sep 2022
Intelligent Traffic Monitoring with Hybrid AI Ehsan Qasemi A. Oltramari 11 3 0 31 Aug 2022
SoK: Explainable Machine Learning for Computer Security Applications A. Nadeem D. Vos Clinton Cao Luca Pajola Simon Dieck Robert Baumgartner S. Verwer 29 40 0 22 Aug 2022
Causality-Inspired Taxonomy for Explainable Artificial Intelligence Pedro C. Neto Tiago B. Gonccalves João Ribeiro Pinto W. Silva Ana F. Sequeira Arun Ross Jaime S. Cardoso XAI 28 12 0 19 Aug 2022
An Empirical Comparison of Explainable Artificial Intelligence Methods for Clinical Data: A Case Study on Traumatic Brain Injury Amin Nayebi Sindhu Tipirneni Brandon Foreman Chandan K. Reddy V. Subbian 26 3 0 13 Aug 2022
An Interpretability Evaluation Benchmark for Pre-trained Language Models Ya-Ming Shen Lijie Wang Ying Chen Xinyan Xiao Jing Liu Hua-Hong Wu 31 4 0 28 Jul 2022
LightX3ECG: A Lightweight and eXplainable Deep Learning System for 3-lead Electrocardiogram Classification Khiem H. Le Hieu H. Pham Thao BT. Nguyen Tu Nguyen T. Thanh Cuong D. Do 18 34 0 25 Jul 2022
A general-purpose method for applying Explainable AI for Anomaly Detection John Sipple Abdou Youssef 22 14 0 23 Jul 2022
A clinically motivated self-supervised approach for content-based image retrieval of CT liver images Kristoffer Wickstrøm Eirik Agnalt Ostmo Keyur Radiya Karl Øyvind Mikalsen Michael C. Kampffmeyer Robert Jenssen SSL 21 13 0 11 Jul 2022
Evaluating Human-like Explanations for Robot Actions in Reinforcement Learning Scenarios Francisco Cruz Charlotte Young Richard Dazeley Peter Vamplew 22 9 0 07 Jul 2022
"Even if ..." -- Diverse Semifactual Explanations of Reject André Artelt Barbara Hammer 33 12 0 05 Jul 2022
FRAME: Evaluating Rationale-Label Consistency Metrics for Free-Text Rationales Aaron Chan Shaoliang Nie Liang Tan Xiaochang Peng Hamed Firooz Maziar Sanjabi Xiang Ren 40 9 0 02 Jul 2022
Why we do need Explainable AI for Healthcare Giovanni Cina Tabea E. Rober Rob Goedhart Ilker Birbil 30 14 0 30 Jun 2022
Auditing Visualizations: Transparency Methods Struggle to Detect Anomalous Behavior Jean-Stanislas Denain Jacob Steinhardt AAML 31 7 0 27 Jun 2022
Stop ordering machine learning algorithms by their explainability! A user-centered investigation of performance and explainability L. Herm Kai Heinrich Jonas Wanner Christian Janiesch 13 84 0 20 Jun 2022
Towards ML Methods for Biodiversity: A Novel Wild Bee Dataset and Evaluations of XAI Methods for ML-Assisted Rare Species Annotations Teodor Chiaburu F. Biessmann Frank Haußer 30 2 0 15 Jun 2022
Mediators: Conversational Agents Explaining NLP Model Behavior Nils Feldhus A. Ravichandran Sebastian Möller 27 16 0 13 Jun 2022
Challenges in Applying Explainability Methods to Improve the Fairness of NLP Models Esma Balkir S. Kiritchenko I. Nejadgholi Kathleen C. Fraser 21 36 0 08 Jun 2022
Explainable Artificial Intelligence (XAI) for Internet of Things: A Survey İbrahim Kök Feyza Yıldırım Okay Özgecan Muyanlı S. Özdemir XAI 14 51 0 07 Jun 2022
A Human-Centric Take on Model Monitoring Murtuza N. Shergadwala Himabindu Lakkaraju K. Kenthapadi 37 9 0 06 Jun 2022
Use-Case-Grounded Simulations for Explanation Evaluation Valerie Chen Nari Johnson Nicholay Topin Gregory Plumb Ameet Talwalkar FAtt ELM 20 24 0 05 Jun 2022
OmniXAI: A Library for Explainable AI Wenzhuo Yang Hung Le Tanmay Laud Silvio Savarese S. Hoi SyDa 21 39 0 01 Jun 2022
Attribution-based Explanations that Provide Recourse Cannot be Robust H. Fokkema R. D. Heide T. Erven FAtt 44 18 0 31 May 2022
MACE: An Efficient Model-Agnostic Framework for Counterfactual Explanation Wenzhuo Yang Jia Li Caiming Xiong S. Hoi CML 19 13 0 31 May 2022
Gradient-based Counterfactual Explanations using Tractable Probabilistic Models Xiaoting Shao Kristian Kersting BDL 22 1 0 16 May 2022
Can counterfactual explanations of AI systems' predictions skew lay users' causal intuitions about the world? If so, can we correct for that? Marko Tešić U. Hahn CML 14 5 0 12 May 2022