Steffen Schotthöfer

According to our database, Steffen Schotthöfer authored at least 14 papers between 2021 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

Windowing Regularization Techniques for Unsteady Aerodynamic Shape Optimization.

Steffen Schotthöfer, Beckett Y. Zhou, Tim Albring, Nicolas R. Gauger

CoRR, 2024

GeoLoRA: Geometric integration for parameter efficient fine-tuning.

Steffen Schotthöfer, Emanuele Zangrando, Gianluca Ceruti, Francesco Tudisco, Jonas Kusch

CoRR, 2024

Federated Dynamical Low-Rank Training with Global Loss Convergence Guarantees.

Steffen Schotthöfer, M. Paul Laiu

CoRR, 2024

Structure-preserving neural networks for the regularized entropy-based closure of the Boltzmann moment system.

Steffen Schotthöfer, M. Paul Laiu, Martin Frank, Cory D. Hauck

CoRR, 2024

Structure-Preserving Operator Learning: Modeling the Collision Operator of Kinetic Equations.

Jae Yong Lee, Steffen Schotthöfer, Tianbai Xiao, Sebastian Krumscheid, Martin Frank

CoRR, 2024

Geometry-aware training of factorized layers in tensor Tucker format.

Emanuele Zangrando, Steffen Schotthöfer, Gianluca Ceruti, Jonas Kusch, Francesco Tudisco

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

2023

KiT-RT: An Extendable Framework for Radiative Transfer and Therapy.

Jonas Kusch, Steffen Schotthöfer, Pia Stammer, Jannick Wolters, Tianbai Xiao

ACM Trans. Math. Softw., December, 2023

Predicting continuum breakdown with deep neural networks.

Tianbai Xiao, Steffen Schotthöfer, Martin Frank

J. Comput. Phys., 2023

Conservation properties of the augmented basis update & Galerkin integrator for kinetic problems.

Lukas Einkemmer, Jonas Kusch, Steffen Schotthöfer

CoRR, 2023

Rank-adaptive spectral pruning of convolutional layers during training.

Emanuele Zangrando, Steffen Schotthöfer, Gianluca Ceruti, Jonas Kusch, Francesco Tudisco

CoRR, 2023

2022

Neural network-based, structure-preserving entropy closures for the Boltzmann moment system.

Steffen Schotthöfer, Tianbai Xiao, Martin Frank, Cory D. Hauck

CoRR, 2022

Low-rank lottery tickets: finding efficient low-rank neural networks via matrix differential equations.

Steffen Schotthöfer, Emanuele Zangrando, Jonas Kusch, Gianluca Ceruti, Francesco Tudisco

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Structure Preserving Neural Networks: A Case Study in the Entropy Closure of the Boltzmann Equation.

Steffen Schotthöfer, Tianbai Xiao, Martin Frank, Cory D. Hauck

Proceedings of the International Conference on Machine Learning, 2022

2021

A structure-preserving surrogate model for the closure of the moment system of the Boltzmann equation using convex deep neural networks.

Steffen Schotthöfer, Tianbai Xiao, Martin Frank, Cory D. Hauck

CoRR, 2021