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166 Results
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Workshop
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Uncertainty Quantification for Surface Ozone Emulators using Deep Learning Kelsey Doerksen · Yuliya Marchetti · James Montgomery · Yarin Gal · Freddie Kalaitzis · Kazuyuki Miyazaki · Kevin Bowman · Steven Lu |
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Position Paper On Diagnostic Uncertainty Estimation from Large Language Models: Next-Word Probability Is Not Pre-test Probability Yanjun Gao · Skatje Myers · Shan Chen · Dmitriy Dligach · Timothy Miller · Danielle Bitterman · Guanhua Chen · Anoop Mayampurath · Matthew Churpek · Majid Afshar |
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Computation-Aware Robust Gaussian Processes Marshal Sinaga · Julien Martinelli · Samuel Kaski |
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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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Hi-fi functional priors by learning activations Marcin Sendera · Amin Sorkhei · Tomasz Kuśmierczyk |
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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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(Implicit) Ensembles of Ensembles: Epistemic Uncertainty Collapse in Large Models Andreas Kirsch |
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A Bayesian Approach Towards Crowdsourcing the Truths from LLMs Peiran Yao · Jerin George Mathew · Shehraj Singh · Donatella Firmani · Denilson Barbosa |
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Probabilistic predictions with Fourier neural operators Christopher Bülte · Philipp Scholl · Gitta Kutyniok |
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NODE-GAMLSS: Interpretable Uncertainty Modelling via Deep Distributional Regression Ananyapam De · Anton Thielmann · Benjamin Säfken |
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Bayesian Outcome Weighted Learning Nikki Freeman · Sophia Yazzourh |
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Estimating protein flexibility via uncertainty quantification of structure prediction models Charlotte Sweeney · Nele Quast · Fabian Spoendlin · Yee Whye Teh |