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Oral
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Wed 15:05
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Scalable Training of Inference Networks for Gaussian-Process Models
Jiaxin Shi · Mohammad Emtiyaz Khan · Jun Zhu
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Poster
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Wed 18:30
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Scalable Training of Inference Networks for Gaussian-Process Models
Jiaxin Shi · Mohammad Emtiyaz Khan · Jun Zhu
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Workshop
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Fri 17:20
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Gaussian Process Optimization with Adaptive Sketching: Scalable and No Regret
Michal Valko
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Oral
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Thu 15:00
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Rates of Convergence for Sparse Variational Gaussian Process Regression
David Burt · Carl E Rasmussen · Mark van der Wilk
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Poster
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Tue 18:30
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Rates of Convergence for Sparse Variational Gaussian Process Regression
David Burt · Carl E Rasmussen · Mark van der Wilk
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Oral
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Wed 11:20
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Graph Convolutional Gaussian Processes
Ian Walker · Ben Glocker
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Oral
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Tue 16:20
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Decomposing feature-level variation with Covariate Gaussian Process Latent Variable Models
Kaspar Märtens · Kieran Campbell · Christopher Yau
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Poster
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Tue 18:30
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Deep Factors for Forecasting
Yuyang Wang · Alex Smola · Danielle Robinson · Jan Gasthaus · Dean Foster · Tim Januschowski
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Poster
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Wed 18:30
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Characterizing Well-Behaved vs. Pathological Deep Neural Networks
Antoine Labatie
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Poster
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Tue 18:30
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Decomposing feature-level variation with Covariate Gaussian Process Latent Variable Models
Kaspar Märtens · Kieran Campbell · Christopher Yau
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Poster
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Wed 18:30
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Distribution calibration for regression
Hao Song · Tom Diethe · Meelis Kull · Peter Flach
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Poster
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Wed 18:30
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Graph Convolutional Gaussian Processes
Ian Walker · Ben Glocker
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