181 citations · 755 across the 107 of their papers we have counts for
65 papers · 1 filter
Particle Filtering for a Class of State-Space Models with Low and Degenerate Observational Noise
Abylay Zhumekenov, Alexandros Beskos, Dan Crisan +2
We consider the discrete-time filtering problem in scenarios where the observation noise is low or degenerate. We focus on the case where the observation equation is a linear funct…
Sequential Markov Chain Monte Carlo for Filtering of State-Space Models with Low or Degenerate Observation Noise
Abylay Zhumekenov, Alexandros Beskos, Dan Crisan +2
We consider the discrete-time filtering problem in scenarios where the observation noise is degenerate or low. More precisely, one is given access to a discrete time observation se…
Unbiased and Multilevel Methods for a Class of Diffusions Partially Observed via Marked Point Processes
Miguel Alvarez, Ajay Jasra, Hamza Ruzayqat
In this article we consider the filtering problem associated to partially observed diffusions, with observations following a marked point process. In the model, the data form a poi…
Bayesian Parameter Inference for Partially Observed Stochastic Volterra Equations
Ajay Jasra, Hamza Ruzayqat, Amin Wu
In this article we consider Bayesian parameter inference for a type of partially observed stochastic Volterra equation (SVE). SVEs are found in many areas such as physics and mathe…
Bayesian Parameter Inference for Partially Observed Diffusions using Multilevel Stochastic Runge-Kutta Methods
Pierre Del Moral, Shulan Hu, Ajay Jasra +2
We consider the problem of Bayesian estimation of static parameters associated to a partially and discretely observed diffusion process. We assume that the exact transition dynamic…
Unbiased Parameter Estimation for Partially Observed Diffusions
Elsiddig Awadelkarim, Ajay Jasra, Hamza Ruzayqat
In this article we consider the estimation of static parameters for partially observed diffusion process with discrete-time observations over a fixed time interval. In particular,…
Multilevel Particle Filters for a Class of Partially Observed Piecewise Deterministic Markov Processes
Ajay Jasra, Kengo Kamatani, Mohamed Maama
In this paper we consider the filtering of a class of partially observed piecewise deterministic Markov processes (PDMPs). In particular, we assume that an ordinary differential eq…
An Improved Unbiased Particle Filter
Ajay Jasra, Mohamed Maama, Hernando Ombao
In this paper we consider the filtering of partially observed multi-dimensional diffusion processes that are observed regularly at discrete times. We assume that, for numerical rea…
Bayesian Parameter Inference for Partially Observed SDEs driven by Fractional Brownian Motion
Mohamed Maama, Ajay Jasra, Hernando Ombao
In this paper we consider Bayesian parameter inference for partially observed fractional Brownian motion (fBM) models. The approach we follow is to time-discretize the hidden proce…
Unbiased Estimation using Underdamped Langevin Dynamics
Hamza Ruzayqat, Neil K. Chada, Ajay Jasra
In this work we consider the unbiased estimation of expectations w.r.t.~probability measures that have non-negative Lebesgue density, and which are known point-wise up-to a normali…
Convergence Speed and Approximation Accuracy of Numerical MCMC
Tiangang Cui, Jing Dong, Ajay Jasra +1
When implementing Markov Chain Monte Carlo (MCMC) algorithms, perturbation caused by numerical errors is sometimes inevitable. This paper studies how perturbation of MCMC affects t…
Bayesian Deep Learning with Multilevel Trace-class Neural Networks
Neil K. Chada, Ajay Jasra, Kody J. H. Law +1
In this article we consider Bayesian inference associated to deep neural networks (DNNs) and in particular, trace-class neural network (TNN) priors which can be preferable to tradi…
Unbiased Estimation using a Class of Diffusion Processes
Hamza Ruzayqat, Alexandros Beskos, Dan Crisan +2
We study the problem of unbiased estimation of expectations with respect to (w.r.t.) a given, general probability measure on that is…
Unbiased Parameter Inference for a Class of Partially Observed Levy-Process Models
Hamza Ruzayqat, Ajay Jasra
We consider the problem of static Bayesian inference for partially observed Levy-process models. We develop a methodology which allows one to infer static parameters and some state…
A Lagged Particle Filter for Stable Filtering of certain High-Dimensional State-Space Models
Hamza Ruzayqat, Aimad Er-Raiy, Alexandros Beskos +3
We consider the problem of high-dimensional filtering of state-space models (SSMs) at discrete times. This problem is particularly challenging as analytical solutions are typically…
Randomized multilevel Monte Carlo for embarrassingly parallel inference
Ajay Jasra, Kody J. H. Law, Alexander Tarakanov +1
This position paper summarizes a recently developed research program focused on inference in the context of data centric science and engineering applications, and forecasts its tra…
Unbiased approximation of posteriors via coupled particle Markov chain Monte Carlo
Willem van den Boom, Ajay Jasra, Maria De Iorio +2
Markov chain Monte Carlo (MCMC) is a powerful methodology for the approximation of posterior distributions. However, the iterative nature of MCMC does not naturally facilitate its…
On Unbiased Estimation for Discretized Models
Jeremy Heng, Ajay Jasra, Kody J. H. Law +1
In this article, we consider computing expectations w.r.t. probability measures which are subject to discretization error. Examples include partially observed diffusion processes o…
Log-Normalization Constant Estimation using the Ensemble Kalman-Bucy Filter with Application to High-Dimensional Models
Dan Crisan, Pierre Del Moral, Ajay Jasra +1
In this article we consider the estimation of the log-normalization constant associated to a class of continuous-time filtering models. In particular, we consider ensemble Kalman-B…
Uncertainty modelling and computational aspects of data association
Jeremie Houssineau, Jiajie Zeng, Ajay Jasra
A novel solution to the smoothing problem for multi-object dynamical systems is proposed and evaluated. The systems of interest contain an unknown and varying number of dynamical o…
Score-Based Parameter Estimation for a Class of Continuous-Time State Space Models
Alexandros Beskos, Dan Crisan, Ajay Jasra +2
We consider the problem of parameter estimation for a class of continuous-time state space models. In particular, we explore the case of a partially observed diffusion, with data a…
Estimation and uncertainty quantification for the output from quantum simulators
Ryan Bennink, Ajay Jasra, Kody J. H. Law +1
The problem of estimating certain distributions over is considered here. The distribution represents a quantum system of qubits, where there are non-trivial depende…
Bridging trees for posterior inference on Ancestral Recombination Graphs
Kari Heine, Alex Beskos, Ajay Jasra +2
We present a new Markov chain Monte Carlo algorithm, implemented in software Arbores, for inferring the history of a sample of DNA sequences. Our principal innovation is a bridging…
Multilevel Particle Filters for Lévy-driven stochastic differential equations
Ajay Jasra, Kody J. H. Law, Prince Peprah Osei
We develop algorithms for computing expectations of the laws of models associated to stochastic differential equations (SDEs) driven by pure Lévy processes. We consider filtering s…