2 papers
cs.LG2025
laplax -- Laplace Approximations with JAX
Tobias Weber, Bálint Mucsányi, Lenard Rommel +4
The Laplace approximation provides a scalable and efficient means of quantifying weight-space uncertainty in deep neural networks, enabling the application of Bayesian tools such a…
cs.LG2025
Flexible and Efficient Probabilistic PDE Solvers through Gaussian Markov Random Fields
Tim Weiland, Marvin Pförtner, Philipp Hennig
Mechanistic knowledge about the physical world is virtually always expressed via partial differential equations (PDEs). Recently, there has been a surge of interest in probabilisti…