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Workshop
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
Workshop
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
Workshop
Computation-Aware Robust Gaussian Processes
Marshal Sinaga · Julien Martinelli · Samuel Kaski
Workshop
Posterior Inferred, Now What? Streamlining Prediction in Bayesian Deep Learning
Rui Li · Marcus Klasson · Arno Solin · Martin Trapp
Workshop
Hi-fi functional priors by learning activations
Marcin Sendera · Amin Sorkhei · Tomasz Kuśmierczyk
Workshop
Two Students: Enabling Uncertainty Quantification in Federated Learning Clients
Cristovão Freitas Iglesias Jr · Sidney Alves de Outeiro · Claudio de Farias · Miodrag Bolic
Workshop
(Implicit) Ensembles of Ensembles: Epistemic Uncertainty Collapse in Large Models
Andreas Kirsch
Workshop
A Bayesian Approach Towards Crowdsourcing the Truths from LLMs
Peiran Yao · Jerin George Mathew · Shehraj Singh · Donatella Firmani · Denilson Barbosa
Workshop
Probabilistic predictions with Fourier neural operators
Christopher Bülte · Philipp Scholl · Gitta Kutyniok
Workshop
NODE-GAMLSS: Interpretable Uncertainty Modelling via Deep Distributional Regression
Ananyapam De · Anton Thielmann · Benjamin Säfken
Workshop
Bayesian Outcome Weighted Learning
Nikki Freeman · Sophia Yazzourh
Workshop
Estimating protein flexibility via uncertainty quantification of structure prediction models
Charlotte Sweeney · Nele Quast · Fabian Spoendlin · Yee Whye Teh