1 citations · 2 across the 12 of their papers we have counts for
5 papers · 1 filter
Efficient Adaptive Data Acquisition via Pretrained Belief Representations
Daolang Huang, Zhuoyue Huang, Conor Hassan +3
Learning effective policies for adaptive data acquisition remains challenging: posterior-based methods rely on surrogate models and posterior approximations that can be misspecifie…
Generative World Modelling for Humanoids: 1X World Model Challenge Technical Report
Riccardo Mereu, Aidan Scannell, Yuxin Hou +6
World models are a powerful paradigm in AI and robotics, enabling agents to reason about the future by predicting visual observations or compact latent states. The 1X World Model C…
Score-Based Density Estimation from Pairwise Comparisons
Petrus Mikkola, Luigi Acerbi, Arto Klami
We study density estimation from pairwise comparisons, motivated by expert knowledge elicitation and learning from human feedback. We relate the unobserved target density to a temp…
Preferential Normalizing Flows
Petrus Mikkola, Luigi Acerbi, Arto Klami
Eliciting a high-dimensional probability distribution from an expert via noisy judgments is notoriously challenging, yet useful for many applications, such as prior elicitation and…
Amortized Bayesian Workflow
Chengkun Li, Aki Vehtari, Paul-Christian Bürkner +3
Bayesian inference often faces a trade-off between computational speed and sampling accuracy. We propose an adaptive workflow that integrates rapid amortized inference with gold-st…