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Poster
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Wed 2:30
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Bayesian Knowledge Distillation: A Bayesian Perspective of Distillation with Uncertainty Quantification
Luyang Fang · Yongkai Chen · Wenxuan Zhong · Ping Ma
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Tutorial
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Mon 4:00
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Distribution-Free Predictive Uncertainty Quantification: Strengths and Limits of Conformal Prediction
Margaux Zaffran · Aymeric Dieuleveut
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Workshop
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Conformalized Credal Set Predictors
Alireza Javanmardi · David Stutz · Eyke Hüllermeier
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Workshop
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Stein Variational Newton Neural Network Ensembles
Klemens Flöge · Muhammad Abdul Moeed · Vincent Fortuin
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Workshop
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Uncertainty-aware Surrogate Models for Airfoil Flow Simulations with Denoising Diffusion Probabilistic Models
Qiang Liu · Nils Thuerey
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Workshop
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Predictive Uncertainties Based on Proper Scoring Rules
Nikita Kotelevskii · Maxim Panov
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Poster
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Tue 2:30
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Using AI Uncertainty Quantification to Improve Human Decision-Making
Laura Marusich · Jonathan Bakdash · Yan Zhou · Murat Kantarcioglu
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Poster
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Thu 2:30
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Second-Order Uncertainty Quantification: A Distance-Based Approach
Yusuf Sale · Viktor Bengs · Michele Caprio · Eyke Hüllermeier
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Workshop
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Reliable Multivariate Deep Regression using Moment-Matching Prior Networks
Qingyi Pan · Ruqi Zhang
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Workshop
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Quantifying Aleatoric and Epistemic Uncertainty: A Credal Approach
Paul Hofman · Yusuf Sale · Eyke Hüllermeier
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Workshop
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Conformal Prediction for Time Series with Transformer
Junghwan Lee · Chen Xu · Yao Xie
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Workshop
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Benchmarking Uncertainty Disentanglement: Specialized Uncertainties for Specialized Tasks
Bálint Mucsányi · Michael Kirchhof · Seong Joon Oh
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