Bayesian probabilistic numerical methods for numerical integration offer...
Control variates can be a powerful tool to reduce the variance of Monte ...
This paper proposes an online, provably robust, and scalable Bayesian
ap...
Likelihood-free inference methods typically make use of a distance betwe...
Multilevel Monte Carlo is a key tool for approximating integrals involvi...
Score-based divergences have been widely used in machine learning and
st...
Discrete state spaces represent a major computational challenge to
stati...
Simulator-based models are models for which the likelihood is intractabl...
Probabilistic numerical methods (PNMs) solve numerical problems via
prob...
Model misspecification can create significant challenges for the
impleme...
Control variates are post-processing tools for Monte Carlo estimators wh...
Intractable generative models are models for which the likelihood is
una...
Stein's method is a collection of tools for analysing distributional
com...
Generalised Bayesian inference updates prior beliefs using a loss functi...
Bayesian neural networks attempt to combine the strong predictive perfor...
Control variates are a well-established tool to reduce the variance of M...
Bayesian quadrature (BQ) is a method for solving numerical integration
p...
Gaussian processes are ubiquitous in statistical analysis, machine learn...
We would like to congratulate the authors of "A Bayesian Conjugate Gradi...
When maximum likelihood estimation is infeasible, one often turns to sco...
While likelihood-based inference and its variants provide a statisticall...
An important task in machine learning and statistics is the approximatio...
This article is the rejoinder for the paper "Probabilistic Integration: ...
An important task in computational statistics and machine learning is to...
Bayesian probabilistic numerical methods are a set of tools providing
po...
The standard Kernel Quadrature method for numerical integration with ran...
Markov Chain Monte Carlo methods have revolutionised mathematical comput...
A research frontier has emerged in scientific computation, wherein numer...
There is renewed interest in formulating integration as an inference pro...