activity
20092026
most citedProbabilistic Numerics and Uncertainty in Computations

140 citations · 1.9k across the 86 of their papers we have counts for

collaborators

95 papers

cs.LG2026

Search Dimension in Unlabeled Projection Pursuit: A Scaling Law for Subspace Restriction

Rares Dimitrie Grozavescu, Mark Girolami

Projection pursuit searches for a direction along which the data look least Gaussian. When the observation space contains a large Gaussian complement, the empirical objective can b…

stat.ME2026

Beyond Laplace: Closed-form wrapped Gaussian posterior approximations on statistical manifolds

Marcelo Hartmann, Luu Hoang Phuc Hau, Anton Mallasto +5

In Bayesian statistics, the Laplace approximation provides a computationally efficient approximation to posterior distributions. However, its Gaussian form restricts it to elliptic…

stat.ML2023

Warped geometric information on the optimisation of Euclidean functions

Marcelo Hartmann, Bernardo Williams, Hanlin Yu +3

We consider the fundamental task of optimising a real-valued function defined in a potentially high-dimensional Euclidean space, such as the loss function in many machine-learning…

physics.data-an2023

Exploring Model Misspecification in Statistical Finite Elements via Shallow Water Equations

Connor Duffin, Paul Branson, Matt Rayson +3

The abundance of observed data in recent years has increased the number of statistical augmentations to complex models across science and engineering. By augmentation we mean coher…

stat.ME2023

Table inference for combinatorial origin-destination choices in agent-based population synthesis

Ioannis Zachos, Theodoros Damoulas, Mark Girolami

A key challenge in agent-based mobility simulations is the synthesis of individual agent socioeconomic profiles. Such profiles include locations of agent activities, which dictate…

stat.ML2023★ 2 cited

Meta-models for transfer learning in source localisation

Lawrence A. Bull, Matthew R. Jones, Elizabeth J. Cross +2

In practice, non-destructive testing (NDT) procedures tend to consider experiments (and their respective models) as distinct, conducted in isolation and associated with independent…