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Affinity Workshop
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Model Averaging to Learn Bayesian Network Structures with Non-Linear Structured Representations
Charupriya Sharma
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Workshop
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Bayesian Sequential Experimental Design for a Partially Linear Model with a Gaussian Process Prior
Shunsuke Horii
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Poster
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Tue 9:00
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Bayesian Optimistic Optimization: Optimistic Exploration for Model-based Reinforcement Learning
Chenyang Wu · Tianci Li · Zongzhang Zhang · Yang Yu
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Poster
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Tue 9:00
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Learning from Stochastically Revealed Preference
John Birge · Xiaocheng Li · Chunlin Sun
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Poster
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Wed 14:00
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Hedging as Reward Augmentation in Probabilistic Graphical Models
Debarun Bhattacharjya · Radu Marinescu
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Poster
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Tue 9:00
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Deciding What to Model: Value-Equivalent Sampling for Reinforcement Learning
Dilip Arumugam · Benjamin Van Roy
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Poster
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Tue 14:00
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Posterior Collapse of a Linear Latent Variable Model
Zihao Wang · Liu Ziyin
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Workshop
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Bayesian Oracle for bounding information gain in neural encoding models
Konstantin-Klemens Lurz · Mohammad Bashiri · Fabian Sinz
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Poster
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Tue 14:00
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Independence Testing for Bounded Degree Bayesian Networks
Arnab Bhattacharyya · Clément L Canonne · Qiping Yang
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Workshop
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Generalized Predictive Coding: Bayesian Inference in Static and Dynamic models
André Ofner · Beren Millidge · Sebastian Stober
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Poster
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Tue 9:00
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Triangulation candidates for Bayesian optimization
Robert Gramacy · Annie Sauer · Nathan Wycoff
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Poster
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Model-Based Offline Reinforcement Learning with Pessimism-Modulated Dynamics Belief
Kaiyang Guo · Shao Yunfeng · Yanhui Geng
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