447 citations · 2.5k across the 63 of their papers we have counts for
16 papers · 1 filter
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…
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…
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…
Sparse online variational Bayesian regression
Kody J. H. Law, Vitaly Zankin
This work considers variational Bayesian inference as an inexpensive and scalable alternative to a fully Bayesian approach in the context of sparsity-promoting priors. In particula…
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…
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…