3 papers
cs.LG2026
In-Context Learning for Latent Space Bayesian Optimization
Tuan A. Vu, Harri Lähdesmäki, Julien Martinelli
Bayesian optimization (BO) is a central tool for sample-efficient design, and latent-space Bayesian optimization (LSBO) extends it to structured objects such as molecules and prote…
cs.LG2026
Upper Entropy for 2-Monotone Lower Probabilities
Tuan-Anh Vu, Sébastien Destercke, Frédéric Pichon
Uncertainty quantification is a key aspect in many tasks such as model selection/regularization, or quantifying prediction uncertainties to perform active learning or OOD detection…
stat.ML2026
Time-Aware Latent Space Bayesian Optimization
Tuan A. Vu, Julien Martinelli, Harri Lähdesmäki
Latent-space Bayesian optimization (LSBO) extends Bayesian optimization to structured domains, such as molecular design, by searching in the continuous latent space of a generative…