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Data-centric Prediction Explanation via Kernelized Stein Discrepancy

22 March 2024

Papers citing "Data-centric Prediction Explanation via Kernelized Stein Discrepancy"

21 / 21 papers shown

Title
Nyström Kernel Stein Discrepancy Florian Kalinke Zoltan Szabo Bharath K. Sriperumbudur 100 1 0 12 Jun 2024
Latent Concept-based Explanation of NLP Models Xuemin Yu Fahim Dalvi Nadir Durrani Marzia Nouri Hassan Sajjad LRM FAtt 59 3 0 18 Apr 2024
Sample based Explanations via Generalized Representers Che-Ping Tsai Chih-Kuan Yeh Pradeep Ravikumar FAtt 93 9 0 27 Oct 2023
TRAK: Attributing Model Behavior at Scale Sung Min Park Kristian Georgiev Andrew Ilyas Guillaume Leclerc Aleksander Madry TDI 120 156 0 24 Mar 2023
If Influence Functions are the Answer, Then What is the Question? Juhan Bae Nathan Ng Alston Lo Marzyeh Ghassemi Roger C. Grosse TDI 108 104 0 12 Sep 2022
Adapting and Evaluating Influence-Estimation Methods for Gradient-Boosted Decision Trees Jonathan Brophy Zayd Hammoudeh Daniel Lowd TDI 99 22 0 30 Apr 2022
Scaling Up Influence Functions Andrea Schioppa Polina Zablotskaia David Vilar Artem Sokolov TDI 110 106 0 06 Dec 2021
Kernel Stein Discrepancy Descent Anna Korba Pierre-Cyril Aubin-Frankowski Szymon Majewski Pierre Ablin 69 52 0 20 May 2021
HYDRA: Hypergradient Data Relevance Analysis for Interpreting Deep Neural Networks Yuanyuan Chen Boyang Albert Li Han Yu Pengcheng Wu Chunyan Miao TDI 89 42 0 04 Feb 2021
Explaining and Improving Model Behavior with k Nearest Neighbor Representations Nazneen Rajani Ben Krause Wengpeng Yin Tong Niu R. Socher Caiming Xiong FAtt 62 33 0 18 Oct 2020
Stochastic Stein Discrepancies Jackson Gorham Anant Raj Lester W. Mackey 85 38 0 06 Jul 2020
Testing Goodness of Fit of Conditional Density Models with Kernels Wittawat Jitkrittum Heishiro Kanagawa Bernhard Schölkopf 52 28 0 24 Feb 2020
Estimating Training Data Influence by Tracing Gradient Descent G. Pruthi Frederick Liu Mukund Sundararajan Satyen Kale TDI 116 419 0 19 Feb 2020
Minimum Stein Discrepancy Estimators Alessandro Barp François‐Xavier Briol Andrew B. Duncan Mark Girolami Lester W. Mackey 80 93 0 19 Jun 2019
Representer Point Selection for Explaining Deep Neural Networks Chih-Kuan Yeh Joon Sik Kim Ian En-Hsu Yen Pradeep Ravikumar TDI 94 254 0 23 Nov 2018
Neural Tangent Kernel: Convergence and Generalization in Neural Networks Arthur Jacot Franck Gabriel Clément Hongler 288 3,225 0 20 Jun 2018
Distilling a Neural Network Into a Soft Decision Tree Nicholas Frosst Geoffrey E. Hinton 439 639 0 27 Nov 2017
Understanding Black-box Predictions via Influence Functions Pang Wei Koh Percy Liang TDI 229 2,910 0 14 Mar 2017
Stein Variational Gradient Descent: A General Purpose Bayesian Inference Algorithm Qiang Liu Dilin Wang BDL 100 1,094 0 16 Aug 2016
A Kernelized Stein Discrepancy for Goodness-of-fit Tests and Model Evaluation Qiang Liu Jason D. Lee Michael I. Jordan 116 486 0 10 Feb 2016
A Kernel Test of Goodness of Fit Kacper P. Chwialkowski Heiko Strathmann Arthur Gretton BDL 215 328 0 09 Feb 2016