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Workshop
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Fri 11:18
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Uncertainty Disentanglement with Non-stationary Heteroscedastic Gaussian Processes for Active Learning
Zeel B Patel
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Affinity Workshop
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Gaussian Process parameterized Covariance Kernels for Non-stationary Regression
Vidhi Lalchand · Talay Cheema · Laurence Aitchison · Carl Edward Rasmussen
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Workshop
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One-Shot Optimal Design for Gaussian Process Analysis of Randomized Experiments
Jelena Markovic · Qing Feng · Eytan Bakshy
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Poster
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Thu 14:00
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Revisiting Active Sets for Gaussian Process Decoders
Pablo Moreno-Muñoz · Cilie Feldager · Søren Hauberg
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Workshop
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Posterior Consistency for Gaussian Process Surrogate Models with Generalized Observations
Rujian Chen · John Fisher III
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Workshop
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Identifying latent climate signals using sparse hierarchical Gaussian processes
Matt Amos · Thomas Pinder · Paul Young
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Workshop
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Gray-Box Gaussian Processes for Automated Reinforcement Learning
Gresa Shala · André Biedenkapp · Frank Hutter · Josif Grabocka
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Workshop
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Sequential Gaussian Processes for Online Learning of Nonstationary Functions
Michael Minyi Zhang · Bianca Dumitrascu · Sinead Williamson · Barbara Engelhardt
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Poster
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Thu 14:00
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Kernel Interpolation with Sparse Grids
Mohit Yadav · Daniel Sheldon · Cameron Musco
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Workshop
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Expert Selection in Distributed Gaussian Processes: A Multi-label Classification Approach
Hamed Jalali · Gjergji Kasneci
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Workshop
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Identifying latent climate signals using sparse hierarchical Gaussian processes
Matt Amos · Thomas Pinder · Paul Young
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Workshop
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Deep Mahalanobis Gaussian Process
Daniel Augusto de Souza · Diego Mesquita · César Lincoln Mattos · João Paulo Gomes
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