56 citations · 57 across the 5 of their papers we have counts for
7 papers
Bayesian Quadrature: Gaussian Processes for Integration
Maren Mahsereci, Toni Karvonen
Bayesian quadrature is a probabilistic, model-based approach to numerical integration, the estimation of intractable integrals, or expectations. Although Bayesian quadrature was po…
A Dictionary of Closed-Form Kernel Mean Embeddings
François-Xavier Briol, Alexandra Gessner, Toni Karvonen +1
Kernel mean embeddings -- integrals of a kernel with respect to a probability distribution -- are essential in Bayesian quadrature, but also widely used in other computational tool…
Connecting Parameter Magnitudes and Hessian Eigenspaces at Scale using Sketched Methods
Andres Fernandez, Frank Schneider, Maren Mahsereci +1
Recently, it has been observed that when training a deep neural net with SGD, the majority of the loss landscape's curvature quickly concentrates in a tiny *top* eigenspace of the…
Comparing Scale Parameter Estimators for Gaussian Process Interpolation with the Brownian Motion Prior: Leave-One-Out Cross Validation and Maximum Likelihood
Masha Naslidnyk, Motonobu Kanagawa, Toni Karvonen +1
Gaussian process (GP) regression is a Bayesian nonparametric method for regression and interpolation, offering a principled way of quantifying the uncertainties of predicted functi…
Emulation of physical processes with Emukit
Andrei Paleyes, Mark Pullin, Maren Mahsereci +3
Decision making in uncertain scenarios is an ubiquitous challenge in real world systems. Tools to deal with this challenge include simulations to gather information and statistical…
A Fourier State Space Model for Bayesian ODE Filters
Hans Kersting, Maren Mahsereci
Gaussian ODE filtering is a probabilistic numerical method to solve ordinary differential equations (ODEs). It computes a Bayesian posterior over the solution from evaluations of t…