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Exploring new ways: Enforcing representational dissimilarity to learn
  new features and reduce error consistency

Exploring new ways: Enforcing representational dissimilarity to learn new features and reduce error consistency

5 July 2023
Tassilo Wald
Constantin Ulrich
Fabian Isensee
David Zimmerer
Gregor Koehler
Michael Baumgartner
Klaus H. Maier-Hein
    OOD
ArXivPDFHTML

Papers citing "Exploring new ways: Enforcing representational dissimilarity to learn new features and reduce error consistency"

3 / 3 papers shown
Title
Similarity of Neural Network Models: A Survey of Functional and Representational Measures
Similarity of Neural Network Models: A Survey of Functional and Representational Measures
Max Klabunde
Tobias Schumacher
M. Strohmaier
Florian Lemmerich
43
63
0
10 May 2023
Git Re-Basin: Merging Models modulo Permutation Symmetries
Git Re-Basin: Merging Models modulo Permutation Symmetries
Samuel K. Ainsworth
J. Hayase
S. Srinivasa
MoMe
239
313
0
11 Sep 2022
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
1