Robert Salomone | DeepAI

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∙ 07/28/2023

Deep Generative Models, Synthetic Tabular Data, and Differential Privacy: An Overview and Synthesis

This article provides a comprehensive synthesis of the recent developmen...

0 Conor Hassan, et al. ∙

∙ 07/15/2023

The Interpolating Information Criterion for Overparameterized Models

The problem of model selection is considered for the setting of interpol...

0 Liam Hodgkinson, et al. ∙

∙ 04/19/2023

Graph Neural Network-Based Anomaly Detection for River Network Systems

Water is the lifeblood of river networks, and its quality plays a crucia...

0 Katie Buchhorn, et al. ∙

∙ 02/07/2023

Structured variational approximations with skew normal decomposable graphical models

Although there is much recent work developing flexible variational metho...

0 Robert Salomone, et al. ∙

∙ 02/07/2023

Federated Variational Inference Methods for Structured Latent Variable Models

Federated learning methods, that is, methods that perform model training...

0 Conor Hassan, et al. ∙

∙ 11/18/2022

Being Bayesian in the 2020s: opportunities and challenges in the practice of modern applied Bayesian statistics

Building on a strong foundation of philosophy, theory, methods and compu...

0 Joshua J Bon, et al. ∙

∙ 10/22/2022

Transport Reversible Jump Proposals

Reversible jump Markov chain Monte Carlo (RJMCMC) proposals that achieve...

0 Laurence Davies, et al. ∙

∙ 05/19/2022

Continuously-Tempered PDMP Samplers

New sampling algorithms based on simulating continuous-time stochastic p...

0 Matthew Sutton, et al. ∙

∙ 04/05/2021

Spectral Subsampling MCMC for Stationary Multivariate Time Series

Spectral subsampling MCMC was recently proposed to speed up Markov chain...

0 Mattias Villani, et al. ∙

∙ 01/25/2020

The reproducing Stein kernel approach for post-hoc corrected sampling

Stein importance sampling is a widely applicable technique based on kern...

0 Liam Hodgkinson, et al. ∙

∙ 10/30/2019

Spectral Subsampling MCMC for Stationary Time Series

Bayesian inference using Markov Chain Monte Carlo (MCMC) on large datase...

0 Robert Salomone, et al. ∙

∙ 03/29/2019

Implicit Langevin Algorithms for Sampling From Log-concave Densities

For sampling from a log-concave density, we study implicit integrators r...

0 Liam Hodgkinson, et al. ∙

∙ 05/10/2018

Unbiased and Consistent Nested Sampling via Sequential Monte Carlo

We introduce a new class of sequential Monte Carlo methods called Nested...

0 Robert Salomone, et al. ∙

∙ 11/30/2017

Monte Carlo Estimation of the Density of the Sum of Dependent Random Variables

We introduce a novel unbiased estimator for the density of a sum of rand...

0 Robert Salomone, et al. ∙

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