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cs.LG2026
Hierarchical Bayesian Quadrature
Tim Weiland, Toni Karvonen, Philipp Hennig
Numerical integration is a cornerstone of various scientific computing applications, such as engineering simulations and model evidence computations in probabilistic machine learni…
cs.LG2026
Scalable Bayesian Inference for Nonlinear Conservation Laws
Tim Weiland, Philipp Hennig
Nonlinear conservation laws are at the heart of many of the most important dynamical systems in science and engineering. In practical applications, such systems are often subject t…
cs.LG2026
Drifting Fields are not Conservative
Leonard T. Franz, Sebastian Hoffmann, Tim Weiland +2
Drifting models have recently gained attention for generating high-quality samples in a single forward pass. During training, they learn a push-forward map by following a vector-va…