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ORCIDLawrence Murray
Person information
- affiliation: Uppsala University, Sweden
- affiliation (former): University of Oxford, UK
- affiliation (former): CSIRO, Perth, WA, Australia
- affiliation (PhD 2008): University of Edinburgh, UK
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2020 – today
- 2021
[j10]Alix Marie d'Avigneau
, Sumeetpal S. Singh, Lawrence M. Murray:
Anytime parallel tempering. Stat. Comput. 31(6): 74 (2021)- 2020
- [j9]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:
Adapting a home telemonitoring intervention for underserved Hispanic/Latino patients with type 2 diabetes: an acceptability and feasibility study. BMC Medical Informatics Decis. Mak. 20(1): 324 (2020) - [c9]Jan Kudlicka, Lawrence M. Murray, Thomas B. Schön, Fredrik Lindsten:
Particle Filter with Rejection Control and Unbiased Estimator of the Marginal Likelihood. ICASSP 2020: 5860-5864 - [i7]Lawrence M. Murray:
Lazy object copy as a platform for population-based probabilistic programming. CoRR abs/2001.05293 (2020)
2010 – 2019
- 2019
- [c8]Anna Wigren, Riccardo Sven Risuleo, Lawrence Murray, Fredrik Lindsten:
Parameter elimination in particle Gibbs sampling. NeurIPS 2019: 8916-8927 - [c7]Jan Kudlicka, Lawrence M. Murray, Fredrik Ronquist, Thomas B. Schön:
Probabilistic Programming for Birth-Death Models of Evolution Using an Alive Particle Filter with Delayed Sampling. UAI 2019: 679-689 - 2018
- [j8]Lawrence M. Murray, Thomas B. Schön:
Automated learning with a probabilistic programming language: Birch. Annu. Rev. Control. 46: 29-43 (2018) - [c6]Lawrence M. Murray, Daniel Lundén, Jan Kudlicka, David Broman, Thomas B. Schön:
Delayed Sampling and Automatic Rao-Blackwellization of Probabilistic Programs. AISTATS 2018: 1037-1046 - [i6]Lawrence M. Murray, Thomas B. Schön:
Automated learning with a probabilistic programming language: Birch. CoRR abs/1810.01539 (2018) - [i5]Daniel Lundén, David Broman, Fredrik Ronquist, Lawrence M. Murray:
Automatic Alignment of Sequential Monte Carlo Inference in Higher-Order Probabilistic Programs. CoRR abs/1812.07439 (2018) - 2017
- [i4]Thomas B. Schön, Andreas Svensson, Lawrence M. Murray, Fredrik Lindsten:
Probabilistic learning of nonlinear dynamical systems using sequential Monte Carlo. CoRR abs/1703.02419 (2017) - 2016
- [j7]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:
A qualitative analysis to optimize a telemonitoring intervention for heart failure patients from disparity communities. BMC Medical Informatics Decis. Mak. 16: 75 (2016) - [c5]Babak Hodjat, Hormoz Shahrzad, Risto Miikkulainen, Lawrence Murray, Chris C. Holmes:
PRETSL: Distributed Probabilistic Rule Evolution for Time-Series Classification. GPTP 2016: 139-148 - 2015
- [j6]Pierre Del Moral, Lawrence M. Murray:
Sequential Monte Carlo with Highly Informative Observations. SIAM/ASA J. Uncertain. Quantification 3(1): 969-997 (2015) - [j5]Pierre E. Jacob, Lawrence M. Murray, Sylvain Rubenthaler:
Path storage in the particle filter. Stat. Comput. 25(2): 487-496 (2015) - 2013
- [j4]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:
Applications of heterogeneous computing in computational and simulation science. Int. J. Comput. Sci. Eng. 8(3): 240-252 (2013) - [j3]Lawrence M. Murray, Emlyn M. Jones, John S. Parslow:
On Disturbance State-Space Models and the Particle Marginal Metropolis-Hastings Sampler. SIAM/ASA J. Uncertain. Quantification 1(1): 494-521 (2013) - [i3]Lawrence M. Murray, Anthony Lee, Pierre E. Jacob:
Rethinking resampling in the particle filter on graphics processing units. CoRR abs/1301.4019 (2013) - 2012
- [j2]Lawrence Murray:
GPU Acceleration of Runge-Kutta Integrators. IEEE Trans. Parallel Distributed Syst. 23(1): 94-101 (2012) - [i2]Lawrence Murray:
GPU acceleration of the particle filter: the Metropolis resampler. CoRR abs/1202.6163 (2012) - 2011
- [j1]Lawrence Murray, Amos J. Storkey:
Particle Smoothing in Continuous Time: A Fast Approach via Density Estimation. IEEE Trans. Signal Process. 59(3): 1017-1026 (2011) - [c4]Nimalan Nandapalan, Richard P. Brent, Lawrence M. Murray, Alistair P. Rendell:
High-Performance Pseudo-Random Number Generation on Graphics Processing Units. PPAM (1) 2011: 609-618 - [c3]Luke Domanski, Tomasz Bednarz, Tim E. Gureyev, Lawrence Murray, Bevan Emma Huang, John A. Taylor:
Applications of Heterogeneous Computing in Computational and Simulation Science. UCC 2011: 382-389 - [i1]Nimalan Nandapalan, Richard P. Brent, Lawrence M. Murray, Alistair P. Rendell:
High-Performance Pseudo-Random Number Generation on Graphics Processing Units. CoRR abs/1108.0486 (2011)
2000 – 2009
- 2007
- [c2]Lawrence Murray, Amos J. Storkey:
Continuous Time Particle Filtering for fMRI. NIPS 2007: 1049-1056 - 2006
- [c1]Amos J. Storkey, Enrico Simonotto, Heather Whalley, Stephen M. Lawrie, Lawrence Murray, David J. McGonigle:
Learning Structural Equation Models for fMRI. NIPS 2006: 1329-1336
Coauthor Index
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