Author

Benedikt Brantner

h-index 2 View on Semantic Scholar

We have 2 of 6 papers

We haven’t gathered this author’s papers yet. Follow them and we’ll fetch their work.

Not the right person? Other researchers publish under this name.

#machine learning Open access May 2023

Generalizing Adam To Manifolds For Efficiently Training Transformers

A new approach is presented that leverages the special structure of the manifolds which are relevant for optimization of neural networks, such as the Stiefel manifold, the symplectic Stiefel manifold and the Grassmann manifold, which makes the generalization of all steps in the Adam optimizer possible.

Benedikt Brantner · arXiv.org · 6 citations

Preprint Aug 2026

Learning Deterministic and Stochastic Forced Hamiltonian Systems

This work develops a geometric framework for learning deterministic and stochastic forced Hamiltonian systems with neural networks and extends the framework to parameter-dependent systems, leading to Parametric Generalized Forced Hamiltonian Neural Networks (PGFHNNs).

Benedikt Brantner, Tomasz Tyranowski · 0 citations