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NeurIPS 2026Ludwig-Maximilians-Universität MInstitute of Computer Science, LStats Department, LMU MunichL3S Research Center, Leibniz UniDFKI (German Research Center forBayesian & probabilistic methods

Deferred Aggregation in Hierarchical Bayesian Optimization

Valentin Margraf, Jonas Hanselle, Julian Rodemann, Marcel Wever and 2 more

Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026OralLMU Munich, MCMLMohamed bin Zayed University of Technology Innovation InstituteMarburguniversityBayesian & probabilistic methods

The Aleatoric-Epistemic Dichotomy of Uncertainty is Meaningful and Indispensable for Machine Learning

Yusuf Sale, Nikita Kotelevskii, Maxim Panov, Eyke Hüllermeier

Sydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026LMU MunichTU MunichMarburguniversityPhysics-informed ML & PDEs

Conformal Prediction for Time-Dependent PDEs

Joshua Stiller, Annika Schneider, Eyke Hüllermeier

Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026LMU MunichInstitute of Computer Science, LMarburguniversityFeature attribution

OperatorSHAP: Fast and Accurate Shapley Value Estimation for Neural Operators

OperatorSHAP trains grid-agnostic amortized Shapley explainers for neural operators, yielding resolution-consistent attributions that transfer across grids without retraining.

Joshua Stiller, Santo Thies, Felix Czaja, Eyke Hüllermeier

Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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