Dan Crisan

发表

Optimization Based Methods for Partially Observed Chaotic Systems

Alexandros Beskos, Ajay Jasra, Daniel Paulin, 2017, Found. Comput. Math..

Discrete Filtering Using Branching and Interacting Particle Systems

Pierre Del Moral, Terry Lyons, Dan Crisan, 1998 .

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

Joaquín Míguez, Dan Crisan, Inés P. Mariño, 2015, 2015 23rd European Signal Processing Conference (EUSIPCO).

Generalised particle filters with Gaussian measures

Kai Li, Dan Crisan, D. Crisan, 2011, 2011 19th European Signal Processing Conference.

What is a Stochastic Process

Alan Bain, Dan Crisan, J. Doob, 1942 .

Stochastic Analysis and Applications 2014

Thaleia Zariphopoulou, Dan Crisan, Ben Hambly, 2014 .

Score-Based Parameter Estimation for a Class of Continuous-Time State Space Models pdf

Nikolas Kantas, Dan Crisan, Ajay Jasra, 2020, SIAM J. Sci. Comput..

Particle Filters - A Theoretical Perspective

Dan Crisan, D. Crisan, 2001, Sequential Monte Carlo Methods in Practice.

Data Assimilation for a Quasi-Geostrophic Model with Circulation-Preserving Stochastic Transport Noise

Darryl D. Holm, Dan Crisan, Igor Shevchenko, 2019, Journal of Statistical Physics.

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

Alexandros Beskos, Ajay Jasra, Daniel Paulin, 2017, Statistics and Computing.

Numerically Modeling Stochastic Lie Transport in Fluid Dynamics

Colin J. Cotter, Darryl D. Holm, Wei Pan, 2018, Multiscale Model. Simul..

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

Dan Crisan, Jessica G. Gaines, Terry J. Lyons, 1998, SIAM J. Appl. Math..

Minimal Entropy Approximations and Optimal Algorithms

Dan Crisan, Terry J. Lyons, D. Crisan, 2002, Monte Carlo Methods Appl..

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, Darryl D. Holm, Wei Pan, 2020, SIAM/ASA J. Uncertain. Quantification.

On the performance of parallelisation schemes for particle filtering

Joaquín Míguez, Dan Crisan, Gonzalo Rios-Muñoz, 2018, EURASIP J. Adv. Signal Process..

A survey of convergence results on particle filtering methods for practitioners

Arnaud Doucet, Dan Crisan, A. Doucet, 2002, IEEE Trans. Signal Process..

Convergence of Sequential Monte Carlo Methods

Arnaud Doucet, Dan Crisan, A. Doucet, 2007 .

The stochastic filtering problem: a brief historical account

Dan Crisan, D. Crisan, 2014, Journal of Applied Probability.

Solution Properties of a 3D Stochastic Euler Fluid Equation

Darryl D. Holm, Dan Crisan, Franco Flandoli, 2017, J. Nonlinear Sci..

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

Dan Crisan, Salvador Ortiz-Latorre, Alexander Lobbe, 2021, ArXiv.

Parallel sequential Monte Carlo for stochastic gradient-free nonconvex optimization

Ömer Deniz Akyildiz, Joaquín Míguez, Dan Crisan, 2020, Stat. Comput..

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

Petar M. Djuric, Joaquín Míguez, Dan Crisan, 2011, Statistics and Computing.

Problem of nonlinear filtering

Dan Crisan, D. Crisan, 1996 .

Numerical Methods for Solving the Filtering Problem

Alan Bain, Dan Crisan, 2009 .

Stable Approximation Schemes for Optimal Filters

Dan Crisan, Joaquin Miguez, Alberto Lopez-Yela, 2018, SIAM/ASA J. Uncertain. Quantification.

Semi-martingale driven variational principles

Dan Crisan, Oliver D. Street, D. Crisan, 2020, Proceedings of the Royal Society A.

Well-Posedness Properties for a Stochastic Rotating Shallow Water Model

Dan Crisan, Oana Lang, D. Crisan, 2021, Journal of Dynamics and Differential Equations.

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

Dan Crisan, Salvador Ortiz-Latorre, Alexander Lobbe, 2022, Stochastics and Partial Differential Equations: Analysis and Computations.

A Lagged Particle Filter for Stable Filtering of certain High-Dimensional State-Space Models pdf

Alexandros Beskos, Nikolas Kantas, Ajay Jasra, 2021, SIAM/ASA J. Uncertain. Quantification.

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

Dan Crisan, Salvador Ortiz-Latorre, Thomas G. Kurtz, 2021, Journal of Stochastic Analysis.

Breakdown of strong solutions of the Thermal Quasi-Geostrophic equation

Dan Crisan, Prince Romeo Mensah, 2022 .

Solution properties of the incompressible Euler system with rough path advection.

Darryl D. Holm, Dan Crisan, James-Michael Leahy, 2021 .

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

Roland Potthast, Peter Jan van Leeuwen, Dan Crisan, 2021, Frontiers in Applied Mathematics and Statistics.

Theoretical and Computational Analysis of the Thermal Quasi-Geostrophic Model

Darryl D. Holm, Dan Crisan, Wei Pan, 2021, Journal of Nonlinear Science.

New Directions in Rough Path Theory

Massimiliano Gubinelli, Dan Crisan, Thomas Cass, 2021, Oberwolfach Reports.

Score-Based Parameter Estimation for a Class of Continuous-Time State Space Models

Alexandros Beskos, Nikolas Kantas, Ajay Jasra, 2021, SIAM J. Sci. Comput..

On the analytical aspects of inertial particle motion

Dan Crisan, Oliver D. Street, D. Crisan, 2021, Journal of Mathematical Analysis and Applications.

Particle representations for stochastic partial differential equations with boundary conditions

Dan Crisan, Thomas G. Kurtz, Christopher Janjigian, 2016, 1607.08909.

Particle Approximations for a Class of Stochastic Partial Differential Equations

Dan Crisan, 2006 .

Sharp derivative bounds for solutions of degenerate semi-linear partial differential equations

Dan Crisan, François Delarue, D. Crisan, 2012 .

A simple scheme for the parallelization of particle filters and its application to the tracking of complex stochastic systems

Dan Crisan, Gonzalo Rios, Joaquin Miguez, 2014, 1407.8071.

Solving backward stochastic differential equations using the cubature method: Application to nonlinear pricing

Dan Crisan, K. Manolarakis, 2010 .

Numerical method for FBSDEs of McKean–Vlasov type

Dan Crisan, Franccois Delarue, Jean-Franccois Chassagneux, 2017, The Annals of Applied Probability.

Stability of the discrete time filter in terms of the tails of noise distributions

Dan Crisan, K. Heine, 2008 .

A Continuous Time Particle Filter

Dan Crisan, D. Crisan, Alan Bain, 2009 .

Particle filters with random resampling times

Dan Crisan, D. Crisan, O. Obanubi, 2012 .

Solving Backward Stochastic Differential Equations Using the Cubature Method: Application to Nonlinear Pricing

Dan Crisan, D. Crisan, K. Manolarakis, 2010, SIAM J. Financial Math..

Modelling uncertainty using circulation-preserving stochastic transport noise in a 2-layer quasi-geostrophic model

Darryl D. Holm, Dan Crisan, Igor Shevchenko, 2018 .

Unbiased multi-index Monte Carlo

Pierre Del Moral, Ajay Jasra, Jeremie Houssineau, 2017, 1702.03057.

Paris-Princeton Lectures on Mathematical Finance 2013

Philip Protter, Paolo Guasoni, Johannes Muhle-Karbe, 2013 .

Stochastic analysis and applications 2014 : in honour of Terry Lyons

Thaleia Zariphopoulou, Dan Crisan, Ben Hambly, 2014 .

RUNGE-KUTTA SCHEMES FOR BACKWARD STOCHASTIC DIFFERENTIAL EQUATIONS

Dan Crisan, Jean-Franccois Chassagneux, 2014 .

Nonlinear filtering with signal dependent observation noise

Michael A. Kouritzin, Dan Crisan, Jie Xiong, 2009 .

Superprocesses in a Brownian environment

Dan Crisan, D. Crisan, 2004, Proceedings of the Royal Society of London. Series A: Mathematical, Physical and Engineering Sciences.

On a robust version of the integral representation formula of nonlinear filtering

Dan Crisan, J.M.C. Clark, D. Crisan, 2005 .

Cubature Methods and Applications

Dan Crisan, D. Crisan, K. Manolarakis, 2013 .

Numerical solutions for a class of SPDEs over bounded domains

Dan Crisan, Jie Xiong, 2007 .

Particle-kernel estimation of the filter density in state-space models

Dan Crisan, Joaqu'in M'iguez, D. Crisan, 2011, 1111.5866.

Probabilistic methods for semilinear partial differential equations. Applications to finance

Dan Crisan, D. Crisan, K. Manolarakis, 2010 .

CLASSICAL SOLUTIONS TO THE MASTER EQUATION FOR LARGE POPULATION EQUILIBRIA

Dan Crisan, François Delarue, Jean-François Chassagneux, 2014 .

A Kusuoka–Lyons–Victoir particle filter

Dan Crisan, Salvador Ortiz-Latorre, D. Crisan, 2013, Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences.

Particle Approximation of the Filtering Density for State-Space Markov Models in Discrete Time

Joaquín Míguez, Dan Crisan, 2011 .