Stability of model predictive control using Markov Chain Monte Carlo optimisation. - Elilini Siva; Paul Goulart; Jan M. Maciejowski; Nikolas Kantas (ECC, 2009)

Sequential Monte Carlo Methods for High-Dimensional Inverse Problems: A Case Study for the Navier-Stokes Equations. - Nikolas Kantas; Alexandros Beskos; Ajay Jasra (SIAM/ASA J. Uncertain. Quantification, 2014)

Bayesian parameter inference for partially observed stopped processes. - Ajay Jasra; Nikolas Kantas; Adam Persing (Stat. Comput., 2014)

Approximate Inference for Observation-Driven Time Series Models with Intractable Likelihoods. - Ajay Jasra; Nikolas Kantas; Elena Ehrlich (ACM Trans. Model. Comput. Simul., 2014)

On Adaptive Estimation for Dynamic Bernoulli Bandits. - Xue Lu; Niall M. Adams; Nikolas Kantas (CoRR, 2017)

Calculating Principal Eigen-Functions of Non-Negative Integral Kernels: Particle Approximations and Applications. - Nick Whiteley; Nikolas Kantas (Math. Oper. Res., 2017)

Particle Filtering for Stochastic Navier-Stokes Signal Observed with Linear Additive Noise. - Francesc Pons Llopis; Nikolas Kantas; Alexandros Beskos; Ajay Jasra (SIAM J. Sci. Comput., 2018)

The sharp, the flat and the shallow: Can weakly interacting agents learn to escape bad minima? - Nikolas Kantas; Panos Parpas; Grigorios A. Pavliotis (CoRR, 2019)

Score-Based Parameter Estimation for a Class of Continuous-Time State Space Models. - Alexandros Beskos; Dan Crisan; Ajay Jasra; Nikolas Kantas; Hamza M. Ruzayqat (SIAM J. Sci. Comput., 2021)

Joint Entropy Search for Multi-Objective Bayesian Optimization. - Ben Tu; Axel Gandy; Nikolas Kantas; Behrang Shafei (NeurIPS, 2022)

Joint Online Parameter Estimation and Optimal Sensor Placement for the Partially Observed Stochastic Advection-Diffusion Equation. - Louis Sharrock; Nikolas Kantas (SIAM/ASA J. Uncertain. Quantification, 2022)

A Lagged Particle Filter for Stable Filtering of Certain High-Dimensional State-Space Models. - Hamza M. Ruzayqat; Aimad Er-Raiy; Alexandros Beskos; Dan Crisan; Ajay Jasra; Nikolas Kantas (SIAM/ASA J. Uncertain. Quantification, 2022)

Privacy Risk for anisotropic Langevin dynamics using relative entropy bounds. - Anastasia Borovykh; Nikolas Kantas; Panos Parpas; Greg Pavliotis (CoRR, 2023)

Multi-Objective Optimization Using the R2 Utility. - Ben Tu; Nikolas Kantas; Robert M. Lee; Behrang Shafei (CoRR, 2023)

Curvature Aligned Simplex Gradient: Principled Sample Set Construction For Numerical Differentiation. - Daniel Lengyel; Panos Parpas; Nikolas Kantas; Nicholas R. Jennings (CoRR, 2023)

Unbiased estimation using a class of diffusion processes. - Hamza M. Ruzayqat; Alexandros Beskos; Dan Crisan; Ajay Jasra; Nikolas Kantas (J. Comput. Phys., 2023)

On the Generalized Langevin Equation for Simulated Annealing. - Martin Chak; Nikolas Kantas; Grigorios A. Pavliotis (SIAM/ASA J. Uncertain. Quantification, 2023)

Random Pareto front surfaces. - Ben Tu; Nikolas Kantas; Robert M. Lee; Behrang Shafei (CoRR, 2024)

Stochastic Mirror Descent for Convex Optimization with Consensus Constraints. - Anastasia Borovykh; Nikolas Kantas; Panos Parpas; Grigorios A. Pavliotis (SIAM J. Appl. Dyn. Syst., 2024)

Scalarisation-based risk concepts for robust multi-objective optimisation. - Ben Tu; Nikolas Kantas; Robert M. Lee; Behrang Shafei (Eur. J. Oper. Res., 2025)

Multiobjective Optimization Using the R2 Utility. - Ben Tu; Nikolas Kantas; Robert M. Lee; Behrang Shafei (SIAM Rev., 2025)