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Workshop
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Regularized KL-Divergence for Well-Defined Function-Space Variational Inference in Bayesian neural networks
Tristan Cinquin · Robert Bamler
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Poster
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Tue 2:30
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Tuning-free Estimation and Inference of Cumulative Distribution Function under Local Differential Privacy
Yi Liu · Qirui Hu · Linglong Kong
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Poster
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Wed 4:30
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State-Free Inference of State-Space Models: The *Transfer Function* Approach
Rom N. Parnichkun · Stefano Massaroli · Alessandro Moro · Jimmy Smith · Ramin Hasani · Mathias Lechner · Qi An · Christopher Re · Hajime Asama · Stefano Ermon · Taiji Suzuki · Michael Poli · Atsushi Yamashita
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Workshop
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EigenVI: score-based variational inference with orthogonal function expansions
Diana Cai · Chirag Modi · Charles Margossian · Robert Gower · David Blei · Lawrence Saul
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Workshop
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Function Space Diversity for Uncertainty Prediction via Repulsive Last-Layer Ensembles
Sophie Steger · Christian Knoll · Bernhard Klein · Holger Fröning · Franz Pernkopf
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Workshop
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State Space Models are Comparable to Transformers in Estimating Functions with Dynamic Smoothness
Naoki Nishikawa · Taiji Suzuki
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Poster
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Tue 2:30
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Learning the Target Network in Function Space
Kavosh Asadi · Yao Liu · Shoham Sabach · Ming Yin · Rasool Fakoor
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Poster
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Thu 4:30
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Position: Optimization in SciML Should Employ the Function Space Geometry
Johannes Müller · Marius Zeinhofer
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Workshop
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Variational Inference Failures Under Model Symmetries: Permutation Invariant Posteriors for Bayesian Neural Networks
Yoav Gelberg · Tycho van der Ouderaa · Mark van der Wilk · Yarin Gal
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Poster
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Tue 2:30
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A New Computationally Efficient Algorithm to solve Feature Selection for Functional Data Classification in High-dimensional Spaces
Tobia Boschi · FRANCESCA BONIN · Rodrigo Ordonez-Hurtado · Alessandra Pascale · Jonathan Epperlein
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