447 citations · 2.5k across the 63 of their papers we have counts for
6 papers · 1 filter
A Bayesian analysis of classical shadows
Joseph M. Lukens, Kody J. H. Law, Ryan S. Bennink
The method of classical shadows heralds unprecedented opportunities for quantum estimation with limited measurements [H.-Y. Huang, R. Kueng, and J. Preskill, Nat. Phys. 16, 1050 (2…
Fast Deep Mixtures of Gaussian Process Experts
Clement Etienam, Kody Law, Sara Wade +1
Mixtures of experts have become an indispensable tool for flexible modelling in a supervised learning context, allowing not only the mean function but the entire density of the out…
Unbiased Estimation of the Gradient of the Log-Likelihood in Inverse Problems
Ajay Jasra, Kody J. H. Law, Deng Lu
We consider the problem of estimating a parameter associated to a Bayesian inverse problem. Treating the unknown initial condition as a nuisance parameter, typically one must resor…
Reconstruction of effective potential from statistical analysis of dynamic trajectories
Ali Yousefzadi Nobakht, Ondrej Dyck, David B. Lingerfelt +8
The broad incorporation of microscopic methods is yielding a wealth of information on atomic and mesoscale dynamics of individual atoms, molecules, and particles on surfaces and in…
A practical and efficient approach for Bayesian quantum state estimation
Joseph M. Lukens, Kody J. H. Law, Ajay Jasra +1
Bayesian inference is a powerful paradigm for quantum state tomography, treating uncertainty in meaningful and informative ways. Yet the numerical challenges associated with sampli…
Unbiased Filtering of a Class of Partially Observed Diffusions
Ajay Jasra, Kody Law, Fangyuan Yu
In this article we consider a Monte Carlo-based method to filter partially observed diffusions observed at regular and discrete times. Given access only to Euler discretizations of…