Author

Sebastian Peitz

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Review Open access Aug 2026

Common Pitfalls to Avoid While Using Multiobjective Optimization in Machine Learning

Abstract. Recently, there has been increasing interest in the application of multiobjective optimization (MOO) in machine learning (ML). This interest is driven by the numerous real-life situations in which multiple objectives must be optimized simultaneously. A key aspect of MOO is the existence of a Pareto set, rath...

Junaid Akhter, Paul Fährmann, Konstantin Sonntag et al. · SIAM Review · 0 citations

#machine learning May 2025

Surrogate Modeling of 3D Rayleigh-Benard Convection with Equivariant Autoencoders

An end-to-end equivariant surrogate model consisting of an equivariant convolutional autoencoder and an equivariant convolutional LSTM using $G$-steerable kernels is presented, demonstrating significant gains in sample and parameter efficiency, as well as a better scaling to more complex dynamics.

Fynn Fromme, Christine Allen-Blanchette, Hans Harder et al. · arXiv.org · 3 citations