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03/06/2023
Bayesian inference with finitely wide neural networks
The analytic inference, e.g. predictive distribution being in closed for...
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03/14/2022
On Connecting Deep Trigonometric Networks with Deep Gaussian Processes: Covariance, Expressivity, and Neural Tangent Kernel
Deep Gaussian Process as a Bayesian learning model is promising because ...
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10/01/2021
Conditional Deep Gaussian Processes: empirical Bayes hyperdata learning
It is desirable to combine the expressive power of deep learning with Ga...
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02/07/2020
Multi-source Deep Gaussian Process Kernel Learning
For many problems, relevant data are plentiful but explicit knowledge is...
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05/27/2019
Interpretable deep Gaussian processes
We propose interpretable deep Gaussian Processes (GPs) that combine the ...
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03/09/2018