Ajay Jasra

According to our database, Ajay Jasra authored at least 70 papers between 2006 and 2024.

Collaborative distances:

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

2024

Bayesian parameter inference for partially observed stochastic volterra equations.

Ajay Jasra, Hamza M. Ruzayqat, Amin Wu

Stat. Comput., 2024

Antithetic Multilevel Methods for Elliptic and Hypo-Elliptic Diffusions with Applications.

Yuga Iguchi, Ajay Jasra, Mohamed Maama, Alexandros Beskos

CoRR, 2024

2023

Unbiased Estimation Using Underdamped Langevin Dynamics.

Hamza M. Ruzayqat, Neil K. Chada, Ajay Jasra

SIAM J. Sci. Comput., June, 2023

On Unbiased Estimation for Discretized Models.

Jeremy Heng, Ajay Jasra, Kody J. H. Law, Alexander Tarakanov

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

Bayesian parameter inference for partially observed stochastic differential equations driven by fractional Brownian motion.

Mohamed Maama, Ajay Jasra, Hernando C. Ombao

Stat. Comput., 2023

Unbiased estimation using a class of diffusion processes.

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

J. Comput. Phys., 2023

Unbiased and Multilevel Methods for a Class of Diffusions Partially Observed via Marked Point Processes.

Miguel Alvarez, Ajay Jasra, Hamza M. Ruzayqat

CoRR, 2023

Bayesian Parameter Inference for Partially Observed Diffusions using Multilevel Stochastic Runge-Kutta Methods.

Pierre Del Moral, Shulan Hu, Ajay Jasra, Hamza M. Ruzayqat, Xinyu Wang

CoRR, 2023

Unbiased Parameter Estimation for Partially Observed Diffusions.

Elsiddig Awadelkarim, Ajay Jasra, Hamza M. Ruzayqat

CoRR, 2023

An Improved Unbiased Particle Filter.

Ajay Jasra, Mohamed Maama, Hernando Ombao

CoRR, 2023

Antithetic Multilevel Particle Filters.

Ajay Jasra, Mohamed Maama, Hernando Ombao

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

Multilevel estimation of normalization constants using ensemble Kalman-Bucy filters.

Hamza M. Ruzayqat, Neil K. Chada, Ajay Jasra

Stat. Comput., 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

Unbiased approximation of posteriors via coupled particle Markov chain Monte Carlo.

Willem van den Boom, Ajay Jasra, Maria De Iorio, Alexandros Beskos, Johan Gunnar Eriksson

Stat. Comput., 2022

Unbiased estimation of the gradient of the log-likelihood for a class of continuous-time state-space models.

Marco Ballesio, Ajay Jasra

Monte Carlo Methods Appl., 2022

Multilevel Ensemble Kalman-Bucy Filters.

Neil K. Chada, Ajay Jasra, Fangyuan Yu

SIAM/ASA J. Uncertain. Quantification, 2022

Improved Efficiency of Multilevel Monte Carlo for Stochastic PDE through Strong Pairwise Coupling.

Neil K. Chada, Håkon Hoel, Ajay Jasra, Georgios E. Zouraris

J. Sci. Comput., 2022

A multilevel approach for stochastic nonlinear optimal control.

Ajay Jasra, Jeremy Heng, Yaxian Xu, Adrian N. Bishop

Int. J. Control, 2022

Bayesian Parameter Inference for Partially Observed SDEs driven by Fractional Brownian Motion.

Mohamed Maama, Ajay Jasra, Hernando Ombao

CoRR, 2022

Unbiased Estimation of the Vanilla and Deterministic Ensemble Kalman-Bucy Filters.

Miguel Alvarez, Neil K. Chada, Ajay Jasra

CoRR, 2022

Multilevel Bayesian Deep Neural Networks.

Neil K. Chada, Ajay Jasra, Kody J. H. Law, Sumeetpal S. Singh

CoRR, 2022

Multi-index Sequential Monte Carlo ratio estimators for Bayesian Inverse problems.

Kody J. H. Law, Neil Walton, Shangda Yang, Ajay Jasra

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

Unbiased estimation of the gradient of the log-likelihood in inverse problems.

Ajay Jasra, Kody J. H. Law, Deng Lu

Stat. Comput., 2021

Uncertainty modelling and computational aspects of data association.

Jeremie Houssineau, Jiajie Zeng, Ajay Jasra

Stat. Comput., 2021

Unbiased Inference for Discretely Observed Hidden Markov Model Diffusions.

Neil K. Chada, Jordan Franks, Ajay Jasra, Kody J. H. Law, Matti Vihola

SIAM/ASA J. Uncertain. Quantification, 2021

Unbiased Parameter Inference for a Class of Partially Observed Lévy-Process Models.

Hamza M. Ruzayqat, Ajay Jasra

CoRR, 2021

Unbiased Estimation of the Hessian for Partially Observed Diffusions.

Neil K. Chada, Ajay Jasra, Fangyuan Yu

CoRR, 2021

Multilevel Estimation of Normalization Constants Using the Ensemble Kalman-Bucy Filter.

Hamza M. Ruzayqat, Neil K. Chada, Ajay Jasra

CoRR, 2021

Randomized multilevel Monte Carlo for embarrassingly parallel inference.

Ajay Jasra, Kody J. H. Law, Fangyuan Yu

CoRR, 2021

Randomized Multilevel Monte Carlo for Embarrassingly Parallel Inference.

Ajay Jasra, Kody J. H. Law, Alexander Tarakanov, Fangyuan Yu

Proceedings of the Driving Scientific and Engineering Discoveries Through the Integration of Experiment, Big Data, and Modeling and Simulation, 2021

2020

Multilevel particle filters for the non-linear filtering problem in continuous time.

Ajay Jasra, Fangyuan Yu, Jeremy Heng

Stat. Comput., 2020

Unbiased estimation of the solution to Zakai's equation.

Hamza M. Ruzayqat, Ajay Jasra

Monte Carlo Methods Appl., 2020

A Wasserstein Coupled Particle Filter for Multilevel Estimation.

Marco Ballesio, Ajay Jasra, Erik von Schwerin, Raúl Tempone

CoRR, 2020

Unbiased Filtering of a Class of Partially Observed Diffusions.

Ajay Jasra, Kody J. H. Law, Fangyuan Yu

CoRR, 2020

2019

On Large Lag Smoothing for Hidden Markov Models.

Jeremie Houssineau, Ajay Jasra, Sumeetpal S. Singh

SIAM J. Numer. Anal., 2019

Identification of MultiObject Dynamical Systems: Consistency and Fisher Information.

Jeremie Houssineau, Sumeetpal S. Singh, Ajay Jasra

SIAM J. Control. Optim., 2019

Correction to: Multilevel particle filters for Lévy-driven stochastic differential equations.

Ajay Jasra, Kody J. H. Law, Prince Peprah Osei

Stat. Comput., 2019

Multilevel particle filters for Lévy-driven stochastic differential equations.

Ajay Jasra, Kody J. H. Law, Prince Peprah Osei

Stat. Comput., 2019

Optimization Based Methods for Partially Observed Chaotic Systems.

Daniel Paulin, Ajay Jasra, Dan Crisan, Alexandros Beskos

Found. Comput. Math., 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

Bayesian Static Parameter Estimation for Partially Observed Diffusions via Multilevel Monte Carlo.

Ajay Jasra, Kengo Kamatani, Kody J. H. Law, Yan Zhou

SIAM J. Sci. Comput., 2018

Multilevel Monte Carlo for Smoothing via Transport Methods.

Jeremie Houssineau, Ajay Jasra, Sumeetpal S. Singh

SIAM J. Sci. Comput., 2018

On coupling particle filter trajectories.

Deborshee Sen, Alexandre H. Thiéry, Ajay Jasra

Stat. Comput., 2018

Multilevel particle filters: normalizing constant estimation.

Ajay Jasra, Kengo Kamatani, Prince Peprah Osei, Yan Zhou

Stat. Comput., 2018

Multilevel Sequential Monte Carlo with Dimension-Independent Likelihood-Informed Proposals.

Alexandros Beskos, Ajay Jasra, Kody J. H. Law, Youssef M. Marzouk, Yan Zhou

SIAM/ASA J. Uncertain. Quantification, 2018

2017

Multilevel Sequential Monte Carlo Samplers for Normalizing Constants.

Pierre Del Moral, Ajay Jasra, Kody J. H. Law, Yan Zhou

ACM Trans. Model. Comput. Simul., 2017

Multilevel Particle Filters.

Ajay Jasra, Kengo Kamatani, Kody J. H. Law, Yan Zhou

SIAM J. Numer. Anal., 2017

2016

Monte Carlo algorithms for computing α-permanents.

Junshan Wang, Ajay Jasra

Stat. Comput., 2016

Variational inference for sparse spectrum Gaussian process regression.

Linda S. L. Tan, Victor M. H. Ong, David J. Nott, Ajay Jasra

Stat. Comput., 2016

2015

Sequential Monte Carlo methods for Bayesian elliptic inverse problems.

Alexandros Beskos, Ajay Jasra, Ege A. Muzaffer, Andrew M. Stuart

Stat. Comput., 2015

A Simulation Approach for Change-Points on Phylogenetic Trees.

Adam Persing, Ajay Jasra, Alexandros Beskos, David J. Balding, Maria De Iorio

J. Comput. Biol., 2015

Bayesian Inference for Duplication-Mutation with Complementarity Network Models.

Ajay Jasra, Adam Persing, Alexandros Beskos, Kari Heine, Maria De Iorio

J. Comput. Biol., 2015

On the Behaviour of the Backward Interpretation of Feynman-Kac Formulae Under Verifiable Conditions.

Ajay Jasra

J. Appl. Probab., 2015

Extended finite-time H_∞ control for uncertain switched linear neutral systems with time-varying delays.

Shun Wang, Tiange Shi, Lixian Zhang, Ajay Jasra, Ming Zeng

Neurocomputing, 2015

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

Computational Methods for a Class of Network Models.

Junshan Wang, Ajay Jasra, Maria De Iorio

J. Comput. Biol., 2014

A Bayesian mixture of lasso regressions with t-errors.

Alberto Cozzini, Ajay Jasra, Giovanni Montana, Adam Persing

Comput. Stat. Data Anal., 2014

2013

Model-Based Clustering with gene Ranking using penalized Mixtures of heavy-tailed Distributions.

Alberto Cozzini, Ajay Jasra, Giovanni Montana

J. Bioinform. Comput. Biol., 2013

2012

An adaptive sequential Monte Carlo method for approximate Bayesian computation.

Pierre Del Moral, Arnaud Doucet, Ajay Jasra

Stat. Comput., 2012

Filtering via approximate Bayesian computation.

Ajay Jasra, Sumeetpal S. Singh, James S. Martin, Emma J. McCoy

Stat. Comput., 2012

2011

Stochastic boosting algorithms.

Ajay Jasra, Christopher C. Holmes

Stat. Comput., 2011

2009

DECODE: a new method for discovering clusters of different densities in spatial data.

Tao Pei, Ajay Jasra, David J. Hand, A-Xing Zhu, Chenghu Zhou

Data Min. Knowl. Discov., 2009

2008

Interacting sequential Monte Carlo samplers for trans-dimensional simulation.

Ajay Jasra, Arnaud Doucet, David A. Stephens, Christopher C. Holmes

Comput. Stat. Data Anal., 2008

2007

On population-based simulation for static inference.

Ajay Jasra, David A. Stephens, Christopher C. Holmes

Stat. Comput., 2007

Bayesian Policy Learning with Trans-Dimensional MCMC.

Matt Hoffman, Arnaud Doucet, Nando de Freitas, Ajay Jasra

Proceedings of the Advances in Neural Information Processing Systems 20, 2007

2006

Optimal Filtering For Partially Observed Point Processes Using Trans-Dimensional Sequential Monte Carlo.

Arnaud Doucet, Luis Montesano, Ajay Jasra

Proceedings of the 2006 IEEE International Conference on Acoustics Speech and Signal Processing, 2006