Calculating effective diffusivities in the limit of vanishing molecular diffusion. - Grigorios A. Pavliotis; Andrew M. Stuart; Konstantinos C. Zygalakis (J. Comput. Phys., 2009)

Analysis of Brownian Dynamics Simulations of Reversible Bimolecular Reactions. - Jana Lipková; Konstantinos C. Zygalakis; S. Jonathan Chapman; Radek Erban (SIAM J. Appl. Math., 2011)

On the Existence and the Applications of Modified Equations for Stochastic Differential Equations. - Konstantinos C. Zygalakis (SIAM J. Sci. Comput., 2011)

A higher-order numerical framework for stochastic simulation of chemical reaction systems. - Tamás Székely; Kevin Burrage; Radek Erban; Konstantinos C. Zygalakis (BMC Syst. Biol., 2012)

Numerical Studies of Homogenization under a Fast Cellular Flow. - Gautam Iyer; Konstantinos C. Zygalakis (Multiscale Model. Simul., 2012)

High Weak Order Methods for Stochastic Differential Equations Based on Modified Equations. - Assyr Abdulle; David Cohen; Gilles Vilmart; Konstantinos C. Zygalakis (SIAM J. Sci. Comput., 2012)

Weak Second Order Explicit Stabilized Methods for Stiff Stochastic Differential Equations. - Assyr Abdulle; Gilles Vilmart; Konstantinos C. Zygalakis (SIAM J. Sci. Comput., 2013)

Efficient simulation of stochastic chemical kinetics with the Stochastic Bulirsch-Stoer extrapolation method. - Tamás Székely; Kevin Burrage; Konstantinos C. Zygalakis; Manuel Barrio (BMC Syst. Biol., 2014)

High Order Numerical Approximation of the Invariant Measure of Ergodic SDEs. - Assyr Abdulle; Gilles Vilmart; Konstantinos C. Zygalakis (SIAM J. Numer. Anal., 2014)

Long Time Accuracy of Lie-Trotter Splitting Methods for Langevin Dynamics. - Assyr Abdulle; Gilles Vilmart; Konstantinos C. Zygalakis (SIAM J. Numer. Anal., 2015)

Probabilistic Linear Multistep Methods. - Onur Teymur; Konstantinos Zygalakis; Ben Calderhead (NIPS, 2016)

Hybrid framework for the simulation of stochastic chemical kinetics. - Andrew B. Duncan; Radek Erban; Konstantinos C. Zygalakis (J. Comput. Phys., 2016)

Exploration of the (Non-)Asymptotic Bias and Variance of Stochastic Gradient Langevin Dynamics. - Sebastian J. Vollmer; Konstantinos C. Zygalakis; Yee Whye Teh (J. Mach. Learn. Res., 2016)

Uncertainty Quantification in the Classification of High Dimensional Data. - Andrea L. Bertozzi; Xiyang Luo; Andrew M. Stuart; Konstantinos C. Zygalakis (CoRR, 2017)

Statistical analysis of differential equations: introducing probability measures on numerical solutions. - Patrick R. Conrad; Mark A. Girolami; Simo Särkkä; Andrew M. Stuart; Konstantinos Zygalakis (Stat. Comput., 2017)

Uncertainty Quantification in Graph-Based Classification of High Dimensional Data. - Andrea L. Bertozzi; Xiyang Luo; Andrew M. Stuart; Konstantinos C. Zygalakis (SIAM/ASA J. Uncertain. Quantification, 2018)

Accelerating proximal Markov chain Monte Carlo by using explicit stabilised methods. - Luis Vargas; Marcelo Pereyra; Konstantinos C. Zygalakis (CoRR, 2019)

PDE-Inspired Algorithms for Semi-Supervised Learning on Point Clouds. - Oliver M. Crook; Tim Hurst; Carola-Bibiane Schönlieb; Matthew Thorpe; Konstantinos C. Zygalakis (CoRR, 2019)

Implicit Regularization in Matrix Sensing: A Geometric View Leads to Stronger Results. - Armin Eftekhari; Konstantinos Zygalakis (CoRR, 2020)

A Linear Transportation Lp Distance for Pattern Recognition. - Oliver M. Crook; Mihai Cucuringu; Tim Hurst; Carola-Bibiane Schönlieb; Matthew Thorpe; Konstantinos C. Zygalakis (CoRR, 2020)

Multi-level Monte Carlo methods for the approximation of invariant measures of stochastic differential equations. - Michael B. Giles; Mateusz B. Majka; Lukasz Szpruch; Sebastian J. Vollmer; Konstantinos C. Zygalakis (Stat. Comput., 2020)

Accelerating Proximal Markov Chain Monte Carlo by Using an Explicit Stabilized Method. - Marcelo Pereyra; Luis Vargas Mieles; Konstantinos C. Zygalakis (SIAM J. Imaging Sci., 2020)

Contractivity of Runge-Kutta Methods for Convex Gradient Systems. - Jesús María Sanz-Serna; Konstantinos C. Zygalakis (SIAM J. Numer. Anal., 2020)

Bayesian Imaging With Data-Driven Priors Encoded by Neural Networks: Theory, Methods, and Algorithms. - Matthew Holden; Marcelo Pereyra; Konstantinos C. Zygalakis (CoRR, 2021)

Directed Network Laplacians and Random Graph Models. - Xue Gong; Desmond John Higham; Konstantinos Zygalakis (CoRR, 2021)

Wasserstein distance estimates for the distributions of numerical approximations to ergodic stochastic differential equations. - Jesús María Sanz-Serna; Konstantinos C. Zygalakis (J. Mach. Learn. Res., 2021)

The Connections Between Lyapunov Functions for Some Optimization Algorithms and Differential Equations. - Jesús María Sanz-Serna; Konstantinos C. Zygalakis (SIAM J. Numer. Anal., 2021)

Generative Hypergraph Models and Spectral Embedding. - Xue Gong; Desmond J. Higham; Konstantinos Zygalakis (CoRR, 2022)

Batch Bayesian Optimization via Particle Gradient Flows. - Enrico Crovini; Simon L. Cotter; Konstantinos Zygalakis; Andrew B. Duncan (CoRR, 2022)

Bayesian Imaging with Data-Driven Priors Encoded by Neural Networks. - Matthew Holden; Marcelo Pereyra; Konstantinos C. Zygalakis (SIAM J. Imaging Sci., 2022)

A Hierarchy of Network Models Giving Bistability Under Triadic Closure. - Stefano Di Giovacchino; Desmond J. Higham; Konstantinos C. Zygalakis (Multiscale Model. Simul., 2022)

A Variational Perspective on High-Resolution ODEs. - Hoomaan Maskan; Konstantinos Zygalakis; Alp Yurtsever (NeurIPS, 2023)

Introduction To Gaussian Process Regression In Bayesian Inverse Problems, With New ResultsOn Experimental Design For Weighted Error Measures. - Tapio Helin; Andrew M. Stuart; Aretha L. Teckentrup; Konstantinos Zygalakis (CoRR, 2023)

Backward error analysis and the qualitative behaviour of stochastic optimization algorithms: Application to stochastic coordinate descent. - Stefano Di Giovacchino; Desmond J. Higham; Konstantinos Zygalakis (CoRR, 2023)

The forward-backward envelope for sampling with the overdamped Langevin algorithm. - Armin Eftekhari; Luis Vargas; Konstantinos C. Zygalakis (Stat. Comput., 2023)

Efficient Bayesian Computation for Low-Photon Imaging Problems. - Savvas Melidonis; Paul Dobson; Yoann Altmann; Marcelo Pereyra; Konstantinos Zygalakis (SIAM J. Imaging Sci., 2023)

The Split Gibbs Sampler Revisited: Improvements to Its Algorithmic Structure and Augmented Target Distribution. - Marcelo Pereyra; Luis Vargas Mieles; Konstantinos C. Zygalakis (SIAM J. Imaging Sci., 2023)

A hybrid tau-leap for simulating chemical kinetics with applications to parameter estimation. - Thomas Trigo Trindade; Konstantinos C. Zygalakis (CoRR, 2024)

Higher-order Connection Laplacians for Directed Simplicial Complexes. - Xue Gong; Desmond J. Higham; Konstantinos Zygalakis; Ginestra Bianconi (CoRR, 2024)

Bayesian computation with generative diffusion models by Multilevel Monte Carlo. - Abdul-Lateef Haji-Ali; Marcelo Pereyra; Luke Shaw; Konstantinos Zygalakis (CoRR, 2024)

Accelerated Bayesian Imaging by Relaxed Proximal-Point Langevin Sampling. - Teresa Klatzer; Paul Dobson; Yoann Altmann; Marcelo Pereyra; Jesús María Sanz-Serna; Konstantinos C. Zygalakis (SIAM J. Imaging Sci., 2024)

Empirical Bayesian Imaging With Large-Scale Push-Forward Generative Priors. - Savvas Melidonis; Matthew Holden; Yoann Altmann; Marcelo Pereyra; Konstantinos C. Zygalakis (IEEE Signal Process. Lett., 2024)

A linear transportation Lp distance for pattern recognition. - Oliver M. Crook; Mihai Cucuringu; Tim Hurst; Carola-Bibiane Schönlieb; Matthew Thorpe; Konstantinos C. Zygalakis (Pattern Recognit., 2024)

Gaussian processes for Bayesian inverse problems associated with linear partial differential equations. - Tianming Bai; Aretha L. Teckentrup; Konstantinos C. Zygalakis (Stat. Comput., 2024)

On the Connections between Optimization Algorithms, Lyapunov Functions, and Differential Equations: Theory and Insights. - Paul Dobson; Jesús María Sanz-Serna; Konstantinos C. Zygalakis (SIAM J. Optim., 2025)

Score-Based Denoising Diffusion Models for Photon-Starved Image Restoration Problems. - Savvas Melidonis; Yiming Xi; Konstantinos C. Zygalakis; Yoann Altmann; Marcelo Pereyra (Trans. Mach. Learn. Res., 2025)

Efficient Bayesian Computation Using Plug-and-Play Priors for Poisson Inverse Problems. - Teresa Klatzer; Savvas Melidonis; Marcelo Pereyra; Konstantinos C. Zygalakis (CoRR, 2025)

Hypothesis Testing in Imaging Inverse Problems. - Yiming Xi; Konstantinos Zygalakis; Marcelo Pereyra (CoRR, 2025)