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