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META-ANOVA: Screening interactions for interpretable machine learning

META-ANOVA: Screening interactions for interpretable machine learning

2 August 2024
Daniel A. Serino
Marc L. Klasky
Chanmoo Park
Dongha Kim
Yongdai Kim
ArXivPDFHTML

Papers citing "META-ANOVA: Screening interactions for interpretable machine learning"

5 / 5 papers shown
Title
Self-Interpretable Model with TransformationEquivariant Interpretation
Self-Interpretable Model with TransformationEquivariant Interpretation
Yipei Wang
Xiaoqian Wang
24
23
0
09 Nov 2021
TabTransformer: Tabular Data Modeling Using Contextual Embeddings
TabTransformer: Tabular Data Modeling Using Contextual Embeddings
Xin Huang
A. Khetan
Milan Cvitkovic
Zohar S. Karnin
ViT
LMTD
140
412
0
11 Dec 2020
GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language
  Understanding
GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding
Alex Jinpeng Wang
Amanpreet Singh
Julian Michael
Felix Hill
Omer Levy
Samuel R. Bowman
ELM
294
6,927
0
20 Apr 2018
Methods for Interpreting and Understanding Deep Neural Networks
Methods for Interpreting and Understanding Deep Neural Networks
G. Montavon
Wojciech Samek
K. Müller
FaML
228
2,231
0
24 Jun 2017
Towards A Rigorous Science of Interpretable Machine Learning
Towards A Rigorous Science of Interpretable Machine Learning
Finale Doshi-Velez
Been Kim
XAI
FaML
225
3,658
0
28 Feb 2017
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