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Set Learning for Accurate and Calibrated Models

Set Learning for Accurate and Calibrated Models

5 July 2023
Lukas Muttenthaler
Robert A. Vandermeulen
Qiuyi Zhang
Thomas Unterthiner
Klaus-Robert Muller
ArXivPDFHTML

Papers citing "Set Learning for Accurate and Calibrated Models"

5 / 5 papers shown
Title
Getting aligned on representational alignment
Getting aligned on representational alignment
Ilia Sucholutsky
Lukas Muttenthaler
Adrian Weller
Andi Peng
Andreea Bobu
...
Thomas Unterthiner
Andrew Kyle Lampinen
Klaus-Robert Muller
M. Toneva
Thomas L. Griffiths
54
72
0
18 Oct 2023
Exposing Outlier Exposure: What Can Be Learned From Few, One, and Zero
  Outlier Images
Exposing Outlier Exposure: What Can Be Learned From Few, One, and Zero Outlier Images
Philipp Liznerski
Lukas Ruff
Robert A. Vandermeulen
Billy Joe Franks
Klaus-Robert Muller
Marius Kloft
UQCV
30
44
0
23 May 2022
Weakly-Supervised Disentanglement Without Compromises
Weakly-Supervised Disentanglement Without Compromises
Francesco Locatello
Ben Poole
Gunnar Rätsch
Bernhard Schölkopf
Olivier Bachem
Michael Tschannen
CoGe
OOD
DRL
171
311
0
07 Feb 2020
Simple and Scalable Predictive Uncertainty Estimation using Deep
  Ensembles
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles
Balaji Lakshminarayanan
Alexander Pritzel
Charles Blundell
UQCV
BDL
268
5,635
0
05 Dec 2016
SMOTE: Synthetic Minority Over-sampling Technique
SMOTE: Synthetic Minority Over-sampling Technique
Nitesh V. Chawla
Kevin W. Bowyer
Lawrence Hall
W. Kegelmeyer
AI4TS
160
25,150
0
09 Jun 2011
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