3 papers
physics.comp-ph2026
Mosaic: A Benchmark Suite for Differentiable Physics Solvers
Andrin Rehmann, Heiko Zimmermann, Dion Häfner
Differentiable partial differential equation (PDE) solvers underpin solver-in-the-loop ML training, gradient-based optimal control, and inverse problems, yet the practical cost of…
cs.CE2025
Surrogate-Based Differentiable Pipeline for Shape Optimization
Andrin Rehmann, Nolan Black, Josiah Bjorgaard +5
Gradient-based optimization of engineering designs is limited by non-differentiable components in the typical computer-aided engineering (CAE) workflow, which calculates performanc…
cs.LG2024
Graph Spring Neural ODEs for Link Sign Prediction
Andrin Rehmann, Alexandre Bovet
Signed graphs allow for encoding positive and negative relations between nodes and are used to model various online activities. Node representation learning for signed graphs is a…