B. Nord

Domain Adaptive Graph Neural Networks for Constraining Cosmological Parameters Across Multiple Data Sets

2023

State of the art astronomical simulations have provided datasets which enabled the training of novel deep learning techniques for constraining cosmological parameters. However, differences in subgrid physics implementation and numerical approximations among simulation suites lead …

SIDDA: SInkhorn Dynamic Domain Adaptation for image classification with equivariant neural networks

2025 · Machine Learning Science and Technology

Abstract Modern neural networks (NNs) often do not generalize well in the presence of a "covariate shift''; that is, in situations where the training and test data distributions differ, but the conditional distribution of classification …