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11/02/2021
Spatio-Temporal Variational Gaussian Processes
We introduce a scalable approach to Gaussian process inference that comb...
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11/02/2021
Bayes-Newton Methods for Approximate Bayesian Inference with PSD Guarantees
We formulate natural gradient variational inference (VI), expectation pr...
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03/19/2021
Sparse Algorithms for Markovian Gaussian Processes
Approximate Bayesian inference methods that scale to very large datasets...
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07/12/2020
State Space Expectation Propagation: Efficient Inference Schemes for Temporal Gaussian Processes
We formulate approximate Bayesian inference in non-conjugate temporal an...
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07/09/2020
Fast Variational Learning in State-Space Gaussian Process Models
Gaussian process (GP) regression with 1D inputs can often be performed i...
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06/24/2020
Movement Tracking by Optical Flow Assisted Inertial Navigation
Robust and accurate six degree-of-freedom tracking on portable devices r...
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01/31/2019
End-to-End Probabilistic Inference for Nonstationary Audio Analysis
A typical audio signal processing pipeline includes multiple disjoint an...
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11/06/2018
Unifying Probabilistic Models for Time-Frequency Analysis
In audio signal processing, probabilistic time-frequency models have man...
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02/02/2018