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69 Results
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Workshop
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Two Students: Enabling Uncertainty Quantification in Federated Learning Clients Cristovão Freitas Iglesias Jr · Sidney Alves de Outeiro · Claudio de Farias · Miodrag Bolic |
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Bayesian Optimization of High-dimensional Outputs with Human Feedback Qing Feng · Zhiyuan Jerry Lin · Yujia Zhang · Ben Letham · Jelena Markovic-Voronov · Ryan-Rhys Griffiths · Peter Frazier · Eytan Bakshy |
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Preference-based Multi-Objective Bayesian Optimization with Gradients Joshua Hang Sai Ip · Ankush Chakrabarty · Ali Mesbah · Diego Romeres |
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Meta-Learned Bayesian Optimization for Energy Yield in Inertial Confinement Fusion Vineet Gundecha · Ricardo Luna Gutierrez · Sahand Ghorbanpour · Desik Rengarajan · Rahman Ejaz · Varchas Gopalaswamy · Riccardo Betti · Soumyendu Sarkar |
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Trieste: Efficiently Exploring The Depths of Black-box Functions with TensorFlow Henry Moss · Victor Picheny · Hrvoje Stojic · Sebastian Ober · Artem Artemev · Andrei Paleyes · Sattar Vakili · Stratis Markou · Jixiang Qing · Nasrulloh Loka · Ivo Couckuyt |
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Gradient-free variational learning with conditional mixture networks Conor Heins · Hao Wu · Dimitrije Markovic · Alexander Tschantz · Jeff Beck · Christopher L Buckley |
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Amortizing intractable inference in diffusion models for Bayesian inverse problems Siddarth Venkatraman · Moksh Jain · Luca Scimeca · Minsu Kim · Marcin Sendera · Mohsin Hasan · Luke Rowe · Sarthak Mittal · Pablo Lemos · Emmanuel Bengio · Alexandre Adam · Jarrid Rector-Brooks · Yashar Hezaveh · Laurence Perreault-Levasseur · Yoshua Bengio · Glen Berseth · Nikolay Malkin |
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Had enough of experts? Elicitation and evaluation of Bayesian priors from large language models David Antony Selby · Kai Spriestersbach · Yuichiro Iwashita · Dennis Bappert · Archana Warrier · Sumantrak Mukherjee · Muhammad Asim · Koichi Kise · Sebastian Vollmer |
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Drift-Resilient TabPFN: In-Context Learning Temporal Distribution Shifts on Tabular Data David Schnurr · Kai Helli · Noah Hollmann · Samuel Müller · Frank Hutter |