Interpretable machine learning: definitions, methods, and applications

14 January 2019

Papers citing "Interpretable machine learning: definitions, methods, and applications"

50 / 329 papers shown

Title
Zyxin is all you need: machine learning adherent cell mechanics Matthew S. Schmitt Jonathan Colen S. Sala J. Devany Shailaja Seetharaman M. Gardel Patrick W. Oakes Vincenzo Vitelli AI4CE 19 9 0 01 Mar 2023
Structural Neural Additive Models: Enhanced Interpretable Machine Learning Mattias Luber Anton Thielmann Benjamin Säfken 31 7 0 18 Feb 2023
Derandomized Novelty Detection with FDR Control via Conformal E-values Meshi Bashari Amir Epstein Yaniv Romano Matteo Sesia 26 13 0 14 Feb 2023
A novel approach to generate datasets with XAI ground truth to evaluate image models Miquel Miró-Nicolau Antoni Jaume-i-Capó Gabriel Moyà Alcover 22 4 0 11 Feb 2023
Personalized Interpretable Classification Zengyou He Yifan Tang Yifan Tang Lianyu Hu Yan Liu Yan Liu 25 0 0 06 Feb 2023
Benchmarking sparse system identification with low-dimensional chaos A. Kaptanoglu Lanyue Zhang Zachary G. Nicolaou Urban Fasel Steven L. Brunton 40 20 0 04 Feb 2023
The Contextual Lasso: Sparse Linear Models via Deep Neural Networks Ryan Thompson Amir Dezfouli Robert Kohn 31 4 0 02 Feb 2023
Explainable Deep Reinforcement Learning: State of the Art and Challenges G. Vouros XAI 50 76 0 24 Jan 2023
A Rigorous Uncertainty-Aware Quantification Framework Is Essential for Reproducible and Replicable Machine Learning Workflows Line C. Pouchard Kristofer G. Reyes Francis J. Alexander Byung-Jun Yoon 27 2 0 13 Jan 2023
XDQN: Inherently Interpretable DQN through Mimicking A. Kontogiannis G. Vouros 16 0 0 08 Jan 2023
A Theoretical Framework for AI Models Explainability with Application in Biomedicine Matteo Rizzo Alberto Veneri A. Albarelli Claudio Lucchese Marco Nobile Cristina Conati XAI 27 8 0 29 Dec 2022
Interpretable ML for Imbalanced Data Damien Dablain C. Bellinger Bartosz Krawczyk D. Aha Nitesh V. Chawla 24 1 0 15 Dec 2022
Improving Accuracy Without Losing Interpretability: A ML Approach for Time Series Forecasting Yiqi Sun Zheng Shi Jianshen Zhang Yongzhi Qi Hao Hu Zuo-jun Shen AI4TS 16 0 0 13 Dec 2022
Quant 4.0: Engineering Quantitative Investment with Automated, Explainable and Knowledge-driven Artificial Intelligence Jian Guo Sai Wang L. Ni H. Shum AIFin 19 8 0 13 Dec 2022
Minimax Optimal Estimation of Stability Under Distribution Shift Hongseok Namkoong Yuanzhe Ma Peter Glynn 29 6 0 13 Dec 2022
Measuring the Driving Forces of Predictive Performance: Application to Credit Scoring Hué Sullivan Hurlin Christophe Pérignon Christophe Saurin Sébastien 13 0 0 12 Dec 2022
Truthful Meta-Explanations for Local Interpretability of Machine Learning Models Ioannis Mollas Nick Bassiliades Grigorios Tsoumakas 18 3 0 07 Dec 2022
On the Pointwise Behavior of Recursive Partitioning and Its Implications for Heterogeneous Causal Effect Estimation M. D. Cattaneo Jason M. Klusowski Peter M. Tian 18 4 0 19 Nov 2022
Deep learning methods for drug response prediction in cancer: predominant and emerging trends A. Partin Thomas Brettin Yitan Zhu Oleksandr Narykov Austin R. Clyde Jamie Overbeek Department of Materials Science 6 54 0 18 Nov 2022
Explainable, Domain-Adaptive, and Federated Artificial Intelligence in Medicine A. Chaddad Qizong Lu Jiali Li Y. Katib R. Kateb C. Tanougast Ahmed Bouridane Ahmed Abdulkadir OOD 24 38 0 17 Nov 2022
Comparing Explanation Methods for Traditional Machine Learning Models Part 1: An Overview of Current Methods and Quantifying Their Disagreement Montgomery Flora Corey K. Potvin A. McGovern Shawn Handler FAtt 19 16 0 16 Nov 2022
Using explainability to design physics-aware CNNs for solving subsurface inverse problems J. Crocker Krishna Kumar B. Cox 17 9 0 16 Nov 2022
An Interpretable Hybrid Predictive Model of COVID-19 Cases using Autoregressive Model and LSTM Yangyi Zhang Sui Tang Guo-Ding Yu 24 11 0 14 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
Cross-Subject Emotion Recognition with Sparsely-Labeled Peripheral Physiological Data Using SHAP-Explained Tree Ensembles Feng Zhou Tao Chen Baiying Lei 24 0 0 05 Nov 2022
SoK: Modeling Explainability in Security Analytics for Interpretability, Trustworthiness, and Usability Dipkamal Bhusal Rosalyn Shin Ajay Ashok Shewale M. K. Veerabhadran Michael Clifford Sara Rampazzi Nidhi Rastogi FAtt AAML 32 5 0 31 Oct 2022
Automatic Diagnosis of Myocarditis Disease in Cardiac MRI Modality using Deep Transformers and Explainable Artificial Intelligence M. Jafari A. Shoeibi Navid Ghassemi Jónathan Heras Saiguang Ling ... Shuihua Wang R. Alizadehsani Juan M Gorriz U. Acharya Hamid Alinejad-Rokny MedIm 22 11 0 26 Oct 2022
Convergence Rates of Oblique Regression Trees for Flexible Function Libraries M. D. Cattaneo Rajita Chandak Jason M. Klusowski 42 11 0 26 Oct 2022
BELIEF in Dependence: Leveraging Atomic Linearity in Data Bits for Rethinking Generalized Linear Models Benjamin Brown Kai Zhang Xiao-Li Meng 22 2 0 19 Oct 2022
A Survey on Explainable Anomaly Detection Zhong Li Yuxuan Zhu M. Leeuwen 38 73 0 13 Oct 2022
CLIP-PAE: Projection-Augmentation Embedding to Extract Relevant Features for a Disentangled, Interpretable, and Controllable Text-Guided Face Manipulation Chenliang Zhou Fangcheng Zhong Cengiz Öztireli CLIP 48 19 0 08 Oct 2022
PathFinder: Discovering Decision Pathways in Deep Neural Networks Ozan Irsoy Ethem Alpaydin FAtt 22 0 0 01 Oct 2022
Towards Human-Compatible XAI: Explaining Data Differentials with Concept Induction over Background Knowledge Cara L. Widmer Md Kamruzzaman Sarker Srikanth Nadella Joshua L. Fiechter I. Juvina B. Minnery Pascal Hitzler Joshua Schwartz M. Raymer 34 7 0 27 Sep 2022
Augmenting Interpretable Models with LLMs during Training Chandan Singh Armin Askari R. Caruana Jianfeng Gao 36 37 0 23 Sep 2022
Towards Faithful Model Explanation in NLP: A Survey Qing Lyu Marianna Apidianaki Chris Callison-Burch XAI 109 107 0 22 Sep 2022
Explaining Anomalies using Denoising Autoencoders for Financial Tabular Data Timur Sattarov Dayananda Herurkar Jörn Hees 30 8 0 21 Sep 2022
EMaP: Explainable AI with Manifold-based Perturbations Minh Nhat Vu Huy Mai My T. Thai AAML 35 2 0 18 Sep 2022
Assessment of cognitive characteristics in intelligent systems and predictive ability O. Kubryak Sergey Kovalchuk N. Bagdasaryan 11 1 0 16 Sep 2022
Regulating eXplainable Artificial Intelligence (XAI) May Harm Consumers Behnam Mohammadi Nikhil Malik Timothy P. Derdenger K. Srinivasan 17 1 0 07 Sep 2022
E Pluribus Unum Interpretable Convolutional Neural Networks George Dimas Eirini Cholopoulou D. Iakovidis 15 3 0 10 Aug 2022
Differentially Private Counterfactuals via Functional Mechanism Fan Yang Qizhang Feng Kaixiong Zhou Jiahao Chen Xia Hu 24 8 0 04 Aug 2022
Multi-modal volumetric concept activation to explain detection and classification of metastatic prostate cancer on PSMA-PET/CT Rosa C.J. Kraaijveld M. Philippens W. Eppinga Ina Jurgenliemk-Schulz K. Gilhuijs P. Kroon Bas H. M. van der Velden MedIm 9 2 0 04 Aug 2022
Topological structure of complex predictions Meng Liu T. Dey D. Gleich 28 3 0 28 Jul 2022
TalkToModel: Explaining Machine Learning Models with Interactive Natural Language Conversations Dylan Slack Satyapriya Krishna Himabindu Lakkaraju Sameer Singh 24 74 0 08 Jul 2022
A systematic review of biologically-informed deep learning models for cancer: fundamental trends for encoding and interpreting oncology data Magdalena Wysocka Oskar Wysocki Marie Zufferey Dónal Landers André Freitas AI4CE 48 28 0 02 Jul 2022
Explanatory causal effects for model agnostic explanations Jiuyong Li Ha Xuan Tran T. Le Lin Liu Kui Yu Jixue Liu CML 24 1 0 23 Jun 2022
OpenXAI: Towards a Transparent Evaluation of Model Explanations Chirag Agarwal Dan Ley Satyapriya Krishna Eshika Saxena Martin Pawelczyk Nari Johnson Isha Puri Marinka Zitnik Himabindu Lakkaraju XAI 29 141 0 22 Jun 2022
Extending Process Discovery with Model Complexity Optimization and Cyclic States Identification: Application to Healthcare Processes Liubov Elkhovskaya Alexander Kshenin M. Balakhontceva Sergey Kovalchuk 9 5 0 10 Jun 2022
EiX-GNN : Concept-level eigencentrality explainer for graph neural networks Adrien Raison Pascal Bourdon David Helbert 14 1 0 07 Jun 2022
Disentangling Epistemic and Aleatoric Uncertainty in Reinforcement Learning Bertrand Charpentier Ransalu Senanayake Mykel Kochenderfer Stephan Günnemann PER UD 50 24 0 03 Jun 2022