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23 Results
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Workshop
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Bayesian Treatment of the Spectrum of the Empirical Kernel in (Sub)Linear-Width Neural Networks Ouns El Harzli · Bernardo Grau |
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Workshop
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Improved Depth Estimation of Bayesian Neural Networks Bart van Erp · Bert de Vries |
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Workshop
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Hi-fi functional priors by learning activations Marcin Sendera · Amin Sorkhei · Tomasz Kuśmierczyk |
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Workshop
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Convergence Rates of Bayesian Network Policy Gradient for Cooperative Multi-Agent Reinforcement Learning Dingyang Chen · Zhenyu Zhang · Xiaolong Kuang · Xinyang Shen · Ozalp Ozer · Qi Zhang |
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Workshop
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Variational Last Layers for Bayesian Optimization Paul Brunzema · Mikkel Jordahn · John Willes · Sebastian Trimpe · Jasper Snoek · James Harrison |
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Workshop
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Learning from Less: Bayesian Neural Networks for Optimization Proxy using Limited Labeled Data Parikshit Pareek · Kaarthik Sundar · Deep Deka · Sidhant Misra |
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Workshop
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Uncertainty Modeling in Graph Neural Networks via Stochastic Differential Equations Richard Bergna · Sergio Calvo Ordoñez · Felix Opolka · Pietro Lió · José Miguel Hernández-Lobato |
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Workshop
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Dimension Deficit: Is 3D a Step Too Far for Optimizing Molecules? Andres Guzman-Cordero · Luca Thiede · Gary Tom · Alan Aspuru-Guzik · Felix Strieth-Kalthoff · Agustinus Kristiadi |
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Poster
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Thu 11:00 |
TuneTables: Context Optimization for Scalable Prior-Data Fitted Networks Benjamin Feuer · Robin Schirrmeister · Valeriia Cherepanova · Chinmay Hegde · Frank Hutter · Micah Goldblum · Niv Cohen · Colin White |
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Workshop
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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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Workshop
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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 |