2 papers
stat.ML2026
Decoupled PFNs: Identifiable Epistemic-Aleatoric Decomposition via Structured Synthetic Priors
Richard Bergna, Stefan Depeweg, José Miguel Hernández-Lobato
Prior-Fitted Networks (PFNs) amortize Bayesian prediction by meta-learning over a synthetic task prior, but their standard output is a posterior predictive distribution over noisy…
stat.ML2026
Conditional Diffusion Sampling
Francisco M. Castro-Macías, Pablo Morales-Álvarez, Saifuddin Syed +3
Sampling from unnormalized multimodal distributions with limited density evaluations remains a fundamental challenge in machine learning and natural sciences. Successful approaches…