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Oral
Tue 0:00 Framing RNN as a kernel method: A neural ODE approach
Adeline Fermanian · Pierre Marion · Jean-Philippe Vert · Gérard Biau
Poster
Wed 16:30 Combining Latent Space and Structured Kernels for Bayesian Optimization over Combinatorial Spaces
Aryan Deshwal · Jana Doppa
Poster
Thu 0:30 Active Assessment of Prediction Services as Accuracy Surface Over Attribute Combinations
Vihari Piratla · Soumen Chakrabarti · Sunita Sarawagi
Poster
Wed 0:30 Variational Inference for Continuous-Time Switching Dynamical Systems
Lukas Köhs · Bastian Alt · Heinz Koeppl
Poster
Thu 0:30 A Probabilistic State Space Model for Joint Inference from Differential Equations and Data
Jonathan Schmidt · Nicholas Krämer · Philipp Hennig
Poster
Tue 8:30 An Infinite-Feature Extension for Bayesian ReLU Nets That Fixes Their Asymptotic Overconfidence
Agustinus Kristiadi · Matthias Hein · Philipp Hennig
Poster
Tue 8:30 Efficient methods for Gaussian Markov random fields under sparse linear constraints
David Bolin · Jonas Wallin
Poster
Wed 16:30 The Limitations of Large Width in Neural Networks: A Deep Gaussian Process Perspective
Geoff Pleiss · John Cunningham
Poster
Tue 8:30 Beyond Tikhonov: faster learning with self-concordant losses, via iterative regularization
Gaspard Beugnot · Julien Mairal · Alessandro Rudi
Poster
Tue 8:30 A universal probabilistic spike count model reveals ongoing modulation of neural variability
David Liu · Mate Lengyel
Poster
Fri 8:30 Constrained Two-step Look-Ahead Bayesian Optimization
Yunxiang Zhang · Xiangyu Zhang · Peter Frazier
Poster
Fri 8:30 The Effect of the Intrinsic Dimension on the Generalization of Quadratic Classifiers
Fabian Latorre · Leello Tadesse Dadi · Paul Rolland · Volkan Cevher