Lawrence Murray

According to our database, Lawrence Murray authored at least 24 papers between 2006 and 2021.

Collaborative distances:

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

2021

Anytime parallel tempering.

Alix Marie d'Avigneau, Sumeetpal S. Singh, Lawrence M. Murray

Stat. Comput., 2021

2020

Adapting a home telemonitoring intervention for underserved Hispanic/Latino patients with type 2 diabetes: an acceptability and feasibility study.

Renee Pekmezaris, Myia S. Williams, Briana Pascarelli, Kayla Finuf, Yael T. Harris, Alyson K. Myers, Tonya N. Taylor, Myriam Kline, Vidhi H. Patel, Lawrence M. Murray, Samy I. McFarlane, Karalyn Pappas, Martin L. Lesser, Amgad N. Makaryus, Sabrina Martinez, Andrjez Kozikowski, Jennifer Polo, Josephine Guzman, Roman Zeltser, Jose Marino, Maria Pena, Ralph J. DiClemente, Dilcia Granville

BMC Medical Informatics Decis. Mak., 2020

Lazy object copy as a platform for population-based probabilistic programming.

Lawrence M. Murray

CoRR, 2020

Particle Filter with Rejection Control and Unbiased Estimator of the Marginal Likelihood.

Jan Kudlicka, Lawrence M. Murray, Thomas B. Schön, Fredrik Lindsten

Proceedings of the 2020 IEEE International Conference on Acoustics, 2020

2019

Probabilistic Programming for Birth-Death Models of Evolution Using an Alive Particle Filter with Delayed Sampling.

Jan Kudlicka, Lawrence M. Murray, Fredrik Ronquist, Thomas B. Schön

Proceedings of the Thirty-Fifth Conference on Uncertainty in Artificial Intelligence, 2019

Parameter elimination in particle Gibbs sampling.

Anna Wigren, Riccardo Sven Risuleo, Lawrence Murray, Fredrik Lindsten

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

2018

Automatic Alignment of Sequential Monte Carlo Inference in Higher-Order Probabilistic Programs.

Daniel Lundén, David Broman, Fredrik Ronquist, Lawrence M. Murray

CoRR, 2018

Automated learning with a probabilistic programming language: Birch.

Lawrence M. Murray, Thomas B. Schön

Annu. Rev. Control., 2018

Delayed Sampling and Automatic Rao-Blackwellization of Probabilistic Programs.

Lawrence M. Murray, Daniel Lundén, Jan Kudlicka, David Broman, Thomas B. Schön

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

2017

Probabilistic learning of nonlinear dynamical systems using sequential Monte Carlo.

Thomas B. Schön, Andreas Svensson, Lawrence M. Murray, Fredrik Lindsten

CoRR, 2017

2016

A qualitative analysis to optimize a telemonitoring intervention for heart failure patients from disparity communities.

Renee Pekmezaris, Rebecca M. Schwartz, Tonya N. Taylor, Paola DiMarzio, Christian N. Nouryan, Lawrence Murray, Gary McKenzie, Deborah Ahern, Stacy Castillo, Kathleen Pecinka, Lorinda Bauer, Tito Orona, Amgad N. Makaryus

BMC Medical Informatics Decis. Mak., 2016

PRETSL: Distributed Probabilistic Rule Evolution for Time-Series Classification.

Babak Hodjat, Hormoz Shahrzad, Risto Miikkulainen, Lawrence Murray, Chris C. Holmes

Proceedings of the Genetic Programming Theory and Practice XIV, 2016

2015

Path storage in the particle filter.

Pierre E. Jacob, Lawrence M. Murray, Sylvain Rubenthaler

Stat. Comput., 2015

Sequential Monte Carlo with Highly Informative Observations.

Pierre Del Moral, Lawrence M. Murray

SIAM/ASA J. Uncertain. Quantification, 2015

2013

On Disturbance State-Space Models and the Particle Marginal Metropolis-Hastings Sampler.

Lawrence M. Murray, Emlyn M. Jones, John S. Parslow

SIAM/ASA J. Uncertain. Quantification, 2013

Applications of heterogeneous computing in computational and simulation science.

Luke Domanski, Tomasz Bednarz, Timur Gureyev, Lawrence Murray, Bevan Emma Huang, Yakov Nesterets, Darren Thompson, Emlyn Jones, Colin Cavanagh, Dadong Wang, Pascal Vallotton, Changming Sun, Alex Khassapov, Andrew W. Stevenson, Sheridan Mayo, Matthew Morell, Andrew W. George, John A. Taylor

Int. J. Comput. Sci. Eng., 2013

Rethinking resampling in the particle filter on graphics processing units

Lawrence M. Murray, Anthony Lee, Pierre E. Jacob

CoRR, 2013

2012

GPU Acceleration of Runge-Kutta Integrators.

Lawrence Murray

IEEE Trans. Parallel Distributed Syst., 2012

GPU acceleration of the particle filter: the Metropolis resampler

Lawrence Murray

CoRR, 2012

2011

Particle Smoothing in Continuous Time: A Fast Approach via Density Estimation.

Lawrence Murray, Amos J. Storkey

IEEE Trans. Signal Process., 2011

Applications of Heterogeneous Computing in Computational and Simulation Science.

Luke Domanski, Tomasz Bednarz, Tim E. Gureyev, Lawrence Murray, Bevan Emma Huang, John A. Taylor

Proceedings of the IEEE 4th International Conference on Utility and Cloud Computing, 2011

High-Performance Pseudo-Random Number Generation on Graphics Processing Units.

Nimalan Nandapalan, Richard P. Brent, Lawrence M. Murray, Alistair P. Rendell

Proceedings of the Parallel Processing and Applied Mathematics, 2011

2007

Continuous Time Particle Filtering for fMRI.

Lawrence Murray, Amos J. Storkey

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

2006

Learning Structural Equation Models for fMRI.

Amos J. Storkey, Enrico Simonotto, Heather Whalley, Stephen M. Lawrie, Lawrence Murray, David J. McGonigle

Proceedings of the Advances in Neural Information Processing Systems 19, 2006