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Data-Efficient and Interpretable Tabular Anomaly Detection
v1v2 (latest)

Data-Efficient and Interpretable Tabular Anomaly Detection

3 March 2022
C. Chang
Jinsung Yoon
Sercan O. Arik
Madeleine Udell
Tomas Pfister
ArXiv (abs)PDFHTML

Papers citing "Data-Efficient and Interpretable Tabular Anomaly Detection"

12 / 12 papers shown
Title
GAM Changer: Editing Generalized Additive Models with Interactive
  Visualization
GAM Changer: Editing Generalized Additive Models with Interactive Visualization
Zijie J. Wang
Alex Kale
Harsha Nori
P. Stella
M. Nunnally
Duen Horng Chau
Mihaela Vorvoreanu
Jennifer Wortman Vaughan
R. Caruana
KELM
35
24
0
06 Dec 2021
NODE-GAM: Neural Generalized Additive Model for Interpretable Deep
  Learning
NODE-GAM: Neural Generalized Additive Model for Interpretable Deep Learning
C. Chang
R. Caruana
Anna Goldenberg
AI4CE
93
80
0
03 Jun 2021
COPOD: Copula-Based Outlier Detection
COPOD: Copula-Based Outlier Detection
Zheng Li
Yue Zhao
N. Botta
C. Ionescu
Xiyang Hu
84
287
0
20 Sep 2020
Explainable Deep One-Class Classification
Explainable Deep One-Class Classification
Philipp Liznerski
Lukas Ruff
Robert A. Vandermeulen
Billy Joe Franks
Marius Kloft
Klaus-Robert Muller
69
199
0
03 Jul 2020
How Interpretable and Trustworthy are GAMs?
How Interpretable and Trustworthy are GAMs?
C. Chang
S. Tan
Benjamin J. Lengerich
Anna Goldenberg
R. Caruana
FAtt
121
79
0
11 Jun 2020
Classification-Based Anomaly Detection for General Data
Classification-Based Anomaly Detection for General Data
Liron Bergman
Yedid Hoshen
62
351
0
05 May 2020
FixMatch: Simplifying Semi-Supervised Learning with Consistency and
  Confidence
FixMatch: Simplifying Semi-Supervised Learning with Consistency and Confidence
Kihyuk Sohn
David Berthelot
Chun-Liang Li
Zizhao Zhang
Nicholas Carlini
E. D. Cubuk
Alexey Kurakin
Han Zhang
Colin Raffel
AAML
163
3,578
0
21 Jan 2020
Deep Semi-Supervised Anomaly Detection
Deep Semi-Supervised Anomaly Detection
Lukas Ruff
Robert A. Vandermeulen
Nico Görnitz
Alexander Binder
Emmanuel Müller
K. Müller
Marius Kloft
UQCV
58
548
0
06 Jun 2019
Deep Anomaly Detection Using Geometric Transformations
Deep Anomaly Detection Using Geometric Transformations
I. Golan
Ran El-Yaniv
111
607
0
28 May 2018
Towards Explaining Anomalies: A Deep Taylor Decomposition of One-Class
  Models
Towards Explaining Anomalies: A Deep Taylor Decomposition of One-Class Models
Jacob R. Kauffmann
K. Müller
G. Montavon
DRL
71
96
0
16 May 2018
Accurate, Large Minibatch SGD: Training ImageNet in 1 Hour
Accurate, Large Minibatch SGD: Training ImageNet in 1 Hour
Priya Goyal
Piotr Dollár
Ross B. Girshick
P. Noordhuis
Lukasz Wesolowski
Aapo Kyrola
Andrew Tulloch
Yangqing Jia
Kaiming He
3DH
128
3,688
0
08 Jun 2017
"Why Should I Trust You?": Explaining the Predictions of Any Classifier
"Why Should I Trust You?": Explaining the Predictions of Any Classifier
Marco Tulio Ribeiro
Sameer Singh
Carlos Guestrin
FAttFaML
1.2K
17,071
0
16 Feb 2016
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