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20182025
most citedFully Scalable Gaussian Processes using Subspace Inducing Inputs

2 citations · 2 across the 3 of their papers we have counts for

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stat.ML2021

How Good are Low-Rank Approximations in Gaussian Process Regression?

Constantinos Daskalakis, Petros Dellaportas, Aristeidis Panos

We provide guarantees for approximate Gaussian Process (GP) regression resulting from two common low-rank kernel approximations: based on random Fourier features, and based on trun…

stat.ML2021

Scalable Marked Point Processes for Exchangeable and Non-Exchangeable Event Sequences

Aristeidis Panos, Ioannis Kosmidis, Petros Dellaportas

We adopt the interpretability offered by a parametric, Hawkes-process-inspired conditional probability mass function for the marks and apply variational inference techniques to der…