2 papers
cs.LG2026
Parallel Noising in Neural Markov Logic Networks
Peter Jung, Giuseppe Marra, Ondrej Kuzelka
Neural Markov Logic Networks (NMLNs) are a flexible neurosymbolic relational model. Previous work has shown that, although NMLNs achieve strong performance as generative models for…
physics.optics2026
Physics-constrained neural networks for surrogate modeling of lossless periodic structures
Eric Prehn, Peter Jung
We introduce a physics-constrained neural network (PCNN) for the rapid prediction of rigorous coupled-wave analysis (RCWA) outputs in the form of Jones matrices. Starting from ener…