3 papers
stat.ML2026
Conditional Diffusion Sampling
Francisco M. Castro-MacÃas, Pablo Morales-Ãlvarez, Saifuddin Syed +3
Sampling from unnormalized multimodal distributions with limited density evaluations remains a fundamental challenge in machine learning and natural sciences. Successful approaches…
stat.ML2026
Improving the Linearized Laplace Approximation via Quadratic Approximations
Pedro Jiménez, Luis A. Ortega, Pablo Morales-Ãlvarez +1
Deep neural networks (DNNs) often produce overconfident out-of-distribution predictions, motivating Bayesian uncertainty quantification. The Linearized Laplace Approximation (LLA)…
cs.LG2026
Scalable Linearized Laplace Approximation via Surrogate Neural Kernel
Luis A. Ortega, Simón RodrÃguez-Santana, Daniel Hernández-Lobato
We introduce a scalable method to approximate the kernel of the Linearized Laplace Approximation (LLA). For this, we use a surrogate deep neural network (DNN) that learns a compact…