3 papers
cs.LG2026
Constrained Co-Design for Photonic Bayesian Neural Networks
Hendrik Borras, Xiao Wang, Bernhard Klein +4
Classical neural networks frequently produce overconfident predictions on ambiguous or out-of-distribution (OOD) data, a liability that grows with each AI system deployed in safety…
astro-ph.GA2026
Systematic selection of surrogate models for nonequilibrium chemistry
Robin Janssen, Lorenzo Branca, Tobias Buck
Nonequilibrium chemistry is central to many astrophysical environments but remains a major computational bottleneck in simulations because solving the associated stiff ODE systems…
cs.LG2024
CODES: Benchmarking Coupled ODE Surrogates
Robin Janssen, Immanuel Sulzer, Tobias Buck
We introduce CODES, a benchmark for comprehensive evaluation of surrogate architectures for coupled ODE systems. Besides standard metrics like mean squared error (MSE) and inferenc…