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Workshop
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Sat 9:30
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Invited Talk: Mark van der Wilk - Open Problems in Gaussian Process Approximation and Benchmarking
Mark van der Wilk
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Poster
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Fri 16:30
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Scalable Bayesian Optimization via Focalized Sparse Gaussian Processes
Yunyue Wei · Vincent Zhuang · Saraswati Soedarmadji · Yanan Sui
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Workshop
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Spectral structure learning for clinical time series
Ivan Lerner · Francis Bach · Anita Burgun
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Workshop
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Sun 12:00
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Gaussian Process Predictions with Uncertain Inputs Enabled by Uncertainty-Tracking Microprocessors
Janith Petangoda · Chatura Samarakoon · Phillip Stanley-Marbell
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Workshop
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A scalable Bayesian continual learning framework for online and sequential decision making
Hanwen Xing · Christopher Yau
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Workshop
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Computation-Aware Robust Gaussian Processes
Marshal Sinaga · Julien Martinelli · Samuel Kaski
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Workshop
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Active Learning for Affinity Prediction of Antibodies
Alexandra Gessner · Sebastian Ober · Owen Vickery · Dino Oglic · Talip Ucar
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Poster
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Thu 16:30
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Overfitting Behaviour of Gaussian Kernel Ridgeless Regression: Varying Bandwidth or Dimensionality
Marko Medvedev · Gal Vardi · Nati Srebro
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Workshop
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Big Batch Bayesian Active Learning by Considering Predictive Probabilities
Sebastian Ober · Sam Power · Tom Diethe · Henry Moss
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Workshop
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Efficient Local Unlearning for Gaussian Processes with Out-of-Distribution Data
Juliusz Ziomek · Ilija Bogunovic
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Workshop
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Gaussian Process Conjoint Analysis for Adaptive Marginal Effect Estimation
Yehu Chen · Jacob Montgomery · Roman Garnett
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Poster
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Thu 11:00
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Gaussian Process Bandits for Top-k Recommendations
Mohit Yadav · Cameron Musco · Daniel Sheldon
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