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Position: Why We Must Rethink Empirical Research in Machine Learning

Position: Why We Must Rethink Empirical Research in Machine Learning

3 May 2024
Moritz Herrmann
F. J. D. Lange
Katharina Eggensperger
Giuseppe Casalicchio
Marcel Wever
Matthias Feurer
David Rügamer
Eyke Hüllermeier
A. Boulesteix
Bernd Bischl
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Papers citing "Position: Why We Must Rethink Empirical Research in Machine Learning"

4 / 4 papers shown
Title
Position: Graph Learning Will Lose Relevance Due To Poor Benchmarks
Position: Graph Learning Will Lose Relevance Due To Poor Benchmarks
Maya Bechler-Speicher
Ben Finkelshtein
Fabrizio Frasca
Luis Muller
Jan Tonshoff
...
Michael M. Bronstein
Mathias Niepert
Bryan Perozzi
Mikhail Galkin
Christopher Morris
OOD
94
2
0
21 Feb 2025
Sparsifying Bayesian neural networks with latent binary variables and
  normalizing flows
Sparsifying Bayesian neural networks with latent binary variables and normalizing flows
Lars Skaaret-Lund
G. Storvik
A. Hubin
BDL
UQCV
20
3
0
05 May 2023
A geometric framework for outlier detection in high-dimensional data
A geometric framework for outlier detection in high-dimensional data
Moritz Herrmann
Florian Pfisterer
Fabian Scheipl
19
2
0
01 Jul 2022
A Plea for Neutral Comparison Studies in Computational Sciences
A Plea for Neutral Comparison Studies in Computational Sciences
A. Boulesteix
M. Eugster
33
107
0
13 Aug 2012
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