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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…
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…