61 citations · 164 across the 17 of their papers we have counts for
17 papers
Diffusion Schrödinger Bridges for Bayesian Computation
Jeremy Heng, Valentin De Bortoli, Arnaud Doucet
Denoising diffusion models are a novel class of generative models that have recently become extremely popular in machine learning. In this paper, we describe how such ideas can als…
Computational Doob's h-transforms for Online Filtering of Discretely Observed Diffusions
Nicolas Chopin, Andras Fulop, Jeremy Heng +1
This paper is concerned with online filtering of discretely observed nonlinear diffusion processes. Our approach is based on the fully adapted auxiliary particle filter, which invo…
Efficient Likelihood-based Estimation via Annealing for Dynamic Structural Macrofinance Models
Andras Fulop, Jeremy Heng, Junye Li
Most solved dynamic structural macrofinance models are non-linear and/or non-Gaussian state-space models with high-dimensional and complex structures. We propose an annealed contro…
Simulating Diffusion Bridges with Score Matching
Jeremy Heng, Valentin De Bortoli, Arnaud Doucet +1
We consider the problem of simulating diffusion bridges, which are diffusion processes that are conditioned to initialize and terminate at two given states. The simulation of diffu…
Diffusion Schrödinger Bridge with Applications to Score-Based Generative Modeling
Valentin De Bortoli, James Thornton, Jeremy Heng +1
Progressively applying Gaussian noise transforms complex data distributions to approximately Gaussian. Reversing this dynamic defines a generative model. When the forward noising p…
On Unbiased Score Estimation for Partially Observed Diffusions
Jeremy Heng, Jeremie Houssineau, Ajay Jasra
We consider the problem of statistical inference for a class of partially-observed diffusion processes, with discretely-observed data and finite-dimensional parameters. We construc…
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…
Sequential Monte Carlo algorithms for agent-based models of disease transmission
Nianqiao Ju, Jeremy Heng, Pierre E. Jacob
Agent-based models of disease transmission involve stochastic rules that specify how a number of individuals would infect one another, recover or be removed from the population. Co…
A simple Markov chain for independent Bernoulli variables conditioned on their sum
Jeremy Heng, Pierre E. Jacob, Nianqiao Ju
We consider a vector of independent binary variables, each with a different probability of success. The distribution of the vector conditional on its sum is known as the condit…
An invitation to sequential Monte Carlo samplers
Chenguang Dai, Jeremy Heng, Pierre E. Jacob +1
Statisticians often use Monte Carlo methods to approximate probability distributions, primarily with Markov chain Monte Carlo and importance sampling. Sequential Monte Carlo sample…
Schrödinger Bridge Samplers
Espen Bernton, Jeremy Heng, Arnaud Doucet +1
Consider a reference Markov process with initial distribution and transition kernels , for some . Assume that you are given distribut…
Multilevel Particle Filters for the Non-Linear Filtering Problem in Continuous Time
Ajay Jasra, Fangyuan Yu, Jeremy Heng
In the following article we consider the numerical approximation of the non-linear filter in continuous-time, where the observations and signal follow diffusion processes. Given ac…
A Multilevel Approach for Stochastic Nonlinear Optimal Control
Ajay Jasra, Jeremy Heng, Yaxian Xu +1
We consider a class of finite time horizon nonlinear stochastic optimal control problem, where the control acts additively on the dynamics and the control cost is quadratic. This f…
Clustering Time Series with Nonlinear Dynamics: A Bayesian Non-Parametric and Particle-Based Approach
Alexander Lin, Yingzhuo Zhang, Jeremy Heng +4
We propose a general statistical framework for clustering multiple time series that exhibit nonlinear dynamics into an a-priori-unknown number of sub-groups. Our motivation comes f…
Unbiased Hamiltonian Monte Carlo with couplings
Jeremy Heng, Pierre E. Jacob
We propose a methodology to parallelize Hamiltonian Monte Carlo estimators. Our approach constructs a pair of Hamiltonian Monte Carlo chains that are coupled in such a way that the…
Controlled Sequential Monte Carlo
Jeremy Heng, Adrian N. Bishop, George Deligiannidis +1
Sequential Monte Carlo methods, also known as particle methods, are a popular set of techniques for approximating high-dimensional probability distributions and their normalizing c…
Gibbs flow for approximate transport with applications to Bayesian computation
Jeremy Heng, Arnaud Doucet, Yvo Pokern
Let and be two distributions on the Borel space . Any measurable function …