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Poster
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Thu 11:00
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Principled Bayesian Optimization in Collaboration with Human Experts
Wenjie Xu · Masaki Adachi · Colin Jones · Michael A Osborne
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Workshop
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Inverse-Free Sparse Variational Gaussian Processes
Stefano Cortinovis · Stefanos Eleftheriadis · Laurence Aitchison · James Hensman · Mark van der Wilk
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Workshop
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TR-BEACON: Shedding Light on Efficient Behavior Discovery in High-Dimensional Spaces with Bayesian Novelty Search over Trust Regions
Wei-Ting Tang · Ankush Chakrabarty · Joel Paulson
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Workshop
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Bayesian Optimization for Protein Sequence Design: Back to Simplicity with Gaussian Processes
Carolin Benjamins · Shikha Surana · Oliver Bent · Marius Lindauer · Paul Duckworth
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Workshop
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Mode Collapse in Variational Deep Gaussian Processes
Francisco Sáez-Maldonado · Juan Maroñas · Daniel Hernández-Lobato
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Workshop
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"How Big is Big Enough?'' Adjusting Model Size in Continual Gaussian Processes
Guiomar Pescador-Barrios · Sarah Filippi · Mark van der Wilk
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Workshop
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Bayesian Optimisation for Protein Sequence Design: Gaussian Processes with Zero-Shot Protein Language Model Prior Mean
Carolin Benjamins · Shikha Surana · Oliver Bent · Marius Lindauer · Paul Duckworth
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Poster
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Wed 16:30
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Safe Time-Varying Optimization based on Gaussian Processes with Spatio-Temporal Kernel
Jialin Li · Marta Zagorowska · Giulia De Pasquale · Alisa Rupenyan · John Lygeros
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Competition
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Sat 13:50
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#1st Place- MMGP: a Mesh Morphing Gaussian Process-based machine learning method for regression of physical problems under non-parameterized geometrical variability
Fabien Casenave
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Workshop
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Efficient Bayesian Additive Regression Models For Microbiome and Gene Expression Studies
Tinghua Chen · Michelle Nixon · Justin Silverman
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Workshop
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Scalable Permutation Invariant Multi-Output Gaussian Processes for Cancer Drug Response
Leiv Rønneberg · Vidhi Lalchand
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Poster
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HHD-GP: Incorporating Helmholtz-Hodge Decomposition into Gaussian Processes for Learning Dynamical Systems
Hao Xu · Jia Pan
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