VINE: Visualizing Statistical Interactions in Black Box Models

1 April 2019

Papers citing "VINE: Visualizing Statistical Interactions in Black Box Models"

8 / 8 papers shown

Title
Implet: A Post-hoc Subsequence Explainer for Time Series Models Fanyu Meng Ziwen Kan Shahbaz Rezaei Z. Kong Xin Chen Xin Liu AI4TS 24 0 0 13 May 2025
Why You Should Not Trust Interpretations in Machine Learning: Adversarial Attacks on Partial Dependence Plots Xi Xin Giles Hooker Fei Huang AAML 38 6 0 29 Apr 2024
REPID: Regional Effect Plots with implicit Interaction Detection J. Herbinger Bernd Bischl Giuseppe Casalicchio FAtt 16 15 0 15 Feb 2022
Aligning Eyes between Humans and Deep Neural Network through Interactive Attention Alignment Yuyang Gao Tong Sun Liang Zhao Sungsoo Ray Hong HAI 21 37 0 06 Feb 2022
Explaining Hyperparameter Optimization via Partial Dependence Plots Julia Moosbauer J. Herbinger Giuseppe Casalicchio Marius Lindauer Bernd Bischl 47 56 0 08 Nov 2021
Interactive slice visualization for exploring machine learning models C. Hurley Mark O'Connell Katarina Domijan FAtt 16 9 0 18 Jan 2021
General Pitfalls of Model-Agnostic Interpretation Methods for Machine Learning Models Christoph Molnar Gunnar Konig J. Herbinger Timo Freiesleben Susanne Dandl Christian A. Scholbeck Giuseppe Casalicchio Moritz Grosse-Wentrup B. Bischl FAtt AI4CE 11 135 0 08 Jul 2020
Learning Certifiably Optimal Rule Lists for Categorical Data E. Angelino Nicholas Larus-Stone Daniel Alabi Margo Seltzer Cynthia Rudin 48 195 0 06 Apr 2017