Nikolas Kantas

According to our database, Nikolas Kantas authored at least 21 papers between 2009 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

Multiobjective Optimization Using the R2 Utility.

Ben Tu, Nikolas Kantas, Robert M. Lee, Behrang Shafei

SIAM Rev., 2025

Scalarisation-based risk concepts for robust multi-objective optimisation.

Ben Tu, Nikolas Kantas, Robert M. Lee, Behrang Shafei

Eur. J. Oper. Res., 2025

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

Random Pareto front surfaces.

Ben Tu, Nikolas Kantas, Robert M. Lee, Behrang Shafei

CoRR, 2024

2023

On the Generalized Langevin Equation for Simulated Annealing.

Martin Chak, Nikolas Kantas, Grigorios A. Pavliotis

SIAM/ASA J. Uncertain. Quantification, March, 2023

Unbiased estimation using a class of diffusion processes.

Hamza M. Ruzayqat, Alexandros Beskos, Dan Crisan, Ajay Jasra, Nikolas Kantas

J. Comput. Phys., 2023

Curvature Aligned Simplex Gradient: Principled Sample Set Construction For Numerical Differentiation.

Daniel Lengyel, Panos Parpas, Nikolas Kantas, Nicholas R. Jennings

CoRR, 2023

Multi-Objective Optimization Using the R2 Utility.

Ben Tu, Nikolas Kantas, Robert M. Lee, Behrang Shafei

CoRR, 2023

Privacy Risk for anisotropic Langevin dynamics using relative entropy bounds.

Anastasia Borovykh, Nikolas Kantas, Panos Parpas, Greg Pavliotis

CoRR, 2023

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, March, 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

Joint Entropy Search for Multi-Objective Bayesian Optimization.

Ben Tu, Axel Gandy, Nikolas Kantas, Behrang Shafei

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2021

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

2019

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

2018

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

2017

Calculating Principal Eigen-Functions of Non-Negative Integral Kernels: Particle Approximations and Applications.

Nick Whiteley, Nikolas Kantas

Math. Oper. Res., 2017

On Adaptive Estimation for Dynamic Bernoulli Bandits.

Xue Lu, Niall M. Adams, Nikolas Kantas

CoRR, 2017

2014

Approximate Inference for Observation-Driven Time Series Models with Intractable Likelihoods.

Ajay Jasra, Nikolas Kantas, Elena Ehrlich

ACM Trans. Model. Comput. Simul., 2014

Bayesian parameter inference for partially observed stopped processes.

Ajay Jasra, Nikolas Kantas, Adam Persing

Stat. Comput., 2014

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

2009

Stability of model predictive control using Markov Chain Monte Carlo optimisation.

Elilini Siva, Paul Goulart, Jan M. Maciejowski, Nikolas Kantas

Proceedings of the 10th European Control Conference, 2009