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Workshop
Posterior Inferred, Now What? Streamlining Prediction in Bayesian Deep Learning
Rui Li · Marcus Klasson · Arno Solin · Martin Trapp
Workshop
A Llama Sunk My Battleship! Asking Rational Questions with LLMs via Bayesian Inference
Gabriel Grand · Valerio Pepe · Jacob Andreas · Josh Tenenbaum
Poster
Wed 11:00 A Metalearned Neural Circuit for Nonparametric Bayesian Inference
Jake Snell · Gianluca Bencomo · Tom Griffiths
Workshop
Can Language Models Perform Implicit Bayesian Inference Over User Preference States?
Linlu Qiu · Fei Sha · Kelsey Allen · Yoon Kim · Tal Linzen · Sjoerd van Steenkiste
Poster
Thu 11:00 Hamiltonian Monte Carlo Inference of Marginalized Linear Mixed-Effects Models
Jinlin Lai · Justin Domke · Daniel Sheldon
Workshop
Distributionally Robust Optimisation with Bayesian Ambiguity Sets
Harita Dellaporta · Patrick O&#x27;Hara · Theodoros Damoulas
Poster
Thu 11:00 Unrolled denoising networks provably learn to perform optimal Bayesian inference
Aayush Karan · Kulin Shah · Sitan Chen · Yonina Eldar
Workshop
Amortized Bayesian Workflow (Extended Abstract)
Marvin Schmitt · Chengkun Li · Aki Vehtari · Luigi Acerbi · Paul-Christian Bürkner · Stefan Radev
Workshop
The Art of Knowing When to Stop: Analysis of Optimal Stopping in People and Machines
Fukun Zhang · Bonan Zhao
Poster
Thu 16:30 Bayesian Online Natural Gradient (BONG)
Matt Jones · Peter Chang · Kevin Murphy
Poster
Thu 16:30 Inflationary Flows: Calibrated Bayesian Inference with Diffusion-Based Models
Daniela de Albuquerque · John Pearson
Poster
Fri 16:30 Divide-and-Conquer Predictive Coding: a structured Bayesian inference algorithm
Eli Sennesh · Hao Wu · Tommaso Salvatori