Dan Crisan

According to our database, Dan Crisan authored at least 34 papers between 1998 and 2024.

Collaborative distances:

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

2024

Sequential Discretization Schemes for a Class of Stochastic Differential Equations and their Application to Bayesian Filtering.

Ömer Deniz Akyildiz, Dan Crisan, Joaquín Míguez

SIAM J. Numer. Anal., 2024

Bayesian inference for geophysical fluid dynamics using generative models.

Alexander Lobbe, Dan Crisan, Oana Lang

CoRR, 2024

Generative Modelling of Stochastic Rotating Shallow Water Noise.

Dan Crisan, Oana Lang, Alexander Lobbe

CoRR, 2024

Data assimilation for the stochastic Camassa-Holm equation using particle filtering: a numerical investigation.

Colin John Cotter, Dan Crisan, Maneesh Kumar Singh

CoRR, 2024

2023

Theoretical and Computational Analysis of the Thermal Quasi-Geostrophic Model.

Dan Crisan, Darryl D. Holm, Erwin Luesink, Prince Romeo Mensah, Wei Pan

J. Nonlinear Sci., October, 2023

Modelling Multiperiod Carbon Markets Using Singular Forward-Backward SDEs.

Jean-François Chassagneux, Hinesh Chotai, Dan Crisan

Math. Oper. Res., February, 2023

Unbiased estimation using a class of diffusion processes.

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

J. Comput. Phys., 2023

Comparison of Stochastic Parametrization Schemes using Data Assimilation on Triad Models.

Bertrand Chapron, Dan Crisan, Darryl D. Holm, Oana Lang, Alexander Lobbe, Étienne Mémin

CoRR, 2023

Uniform in time convergence of numerical schemes for stochastic differential equations via Strong Exponential stability: Euler methods, Split-Step and Tamed Schemes.

Letizia Angeli, Dan Crisan, Michela Ottobre

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

A 4D-Var method with flow-dependent background covariances for the shallow-water equations.

Daniel Paulin, Ajay Jasra, Alexandros Beskos, Dan Crisan

Stat. Comput., 2022

Bayesian inference for fluid dynamics: A case study for the stochastic rotating shallow water model.

Oana Lang, Peter Jan van Leeuwen, Dan Crisan, Roland Potthast

Frontiers Appl. Math. Stat., 2022

Theoretical analysis and numerical approximation for the stochastic thermal quasi-geostrophic model.

Dan Crisan, Darryl D. Holm, Oana Lang, Prince Romeo Mensah, Wei Pan

CoRR, 2022

Space-sequential particle filters for high-dimensional dynamical systems described by stochastic differential equations.

Deniz Akyildiz, Dan Crisan, Joaquín Míguez

CoRR, 2022

An application of the splitting-up method for the computation of a neural network representation for the solution for the filtering equations.

Dan Crisan, Alexander Lobbe, Salvador Ortiz-Latorre

CoRR, 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

Particle representation for the solution of the filtering problem. Application to the error expansion of filtering discretizations.

Dan Crisan, Thomas G. Kurtz, Salvador Ortiz-Latorre

CoRR, 2021

Pathwise approximations for the solution of the non-linear filtering problem.

Dan Crisan, Alexander Lobbe, Salvador Ortiz-Latorre

CoRR, 2021

2020

Parallel sequential Monte Carlo for stochastic gradient-free nonconvex optimization.

Ömer Deniz Akyildiz, Dan Crisan, Joaquín Míguez

Stat. Comput., 2020

Stable Approximation Schemes for Optimal Filters.

Dan Crisan, Alberto López-Yela, Joaquín Míguez

SIAM/ASA J. Uncertain. Quantification, 2020

A Particle Filter for Stochastic Advection by Lie Transport: A Case Study for the Damped and Forced Incompressible Two-Dimensional Euler Equation.

Colin J. Cotter, Dan Crisan, Darryl D. Holm, Wei Pan, Igor Shevchenko

SIAM/ASA J. Uncertain. Quantification, 2020

2019

Numerically Modeling Stochastic Lie Transport in Fluid Dynamics.

Colin J. Cotter, Dan Crisan, Darryl D. Holm, Wei Pan, Igor Shevchenko

Multiscale Model. Simul., 2019

Solution Properties of a 3D Stochastic Euler Fluid Equation.

Dan Crisan, Franco Flandoli, Darryl D. Holm

J. Nonlinear Sci., 2019

Optimization Based Methods for Partially Observed Chaotic Systems.

Daniel Paulin, Ajay Jasra, Dan Crisan, Alexandros Beskos

Found. Comput. Math., 2019

Data assimilation for a quasi-geostrophic model with circulation-preserving stochastic transport noise.

Colin J. Cotter, Dan Crisan, Darryl D. Holm, Wei Pan, Igor Shevchenko

CoRR, 2019

2018

On the performance of parallelisation schemes for particle filtering.

Dan Crisan, Joaquín Míguez, Gonzalo Rios-Muñoz

EURASIP J. Adv. Signal Process., 2018

2015

Particle filtering for Bayesian parameter estimation in a high dimensional state space model.

Joaquín Míguez, Dan Crisan, Inés P. Mariño

Proceedings of the 23rd European Signal Processing Conference, 2015

2014

The stochastic filtering problem: a brief historical account.

Dan Crisan

J. Appl. Probab., 2014

2013

On the convergence of two sequential Monte Carlo methods for maximum a posteriori sequence estimation and stochastic global optimization.

Joaquín Míguez, Dan Crisan, Petar M. Djuric

Stat. Comput., 2013

2011

Generalised particle filters with Gaussian measures.

Dan Crisan, Kai Li

Proceedings of the 19th European Signal Processing Conference, 2011

2002

A survey of convergence results on particle filtering methods for practitioners.

Dan Crisan, Arnaud Doucet

IEEE Trans. Signal Process., 2002

Minimal Entropy Approximations and Optimal Algorithms.

Dan Crisan, Terry J. Lyons

Monte Carlo Methods Appl., 2002

2001

Particle Filters - A Theoretical Perspective.

Dan Crisan

Proceedings of the Sequential Monte Carlo Methods in Practice, 2001

1998

Convergence of a Branching Particle Method to the Solution of the Zakai Equation.

Dan Crisan, Jessica G. Gaines, Terry J. Lyons

SIAM J. Appl. Math., 1998