Luke Bornn

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Andrew C. MillerResearch Scientist, AppleVerified email at apple.com
Alexander D'AmourResearch Scientist, Google DeepMindVerified email at google.com
Alexander FranksDepartment of Statistics and Applied Probability, University of California Santa BarbaraVerified email at pstat.ucsb.edu
Charles FarrarLos AlamosVerified email at lanl.gov
Gyuhae ParkChonnam National University, KoreaVerified email at jnu.ac.kr
Arnaud DoucetProfessor of Statistics, University of Oxford & Research Scientist, Google DeepMindVerified email at google.com
James V ZidekProfessor of Statistics, University of British ColumbiaVerified email at stat.ubc.ca
Dawn WoodardDistinguished Engineer, LinkedInVerified email at woodardscience.com
Natesh S. PillaiHarvard UniversityVerified email at fas.harvard.edu
Ryan P. AdamsPrinceton UniversityVerified email at princeton.edu
Greg MoriResearch Director, Borealis AI; Professor, School of Computing Science, Simon Fraser UniversityVerified email at cs.sfu.ca
Sez Atamturktur, Harry and Arlene Sch...Pennsylvania State UniversityVerified email at psu.edu
Raphael GottardoLausanne University Hospital and University of LausanneVerified email at chuv.ch
Frederick TungBorealis AIVerified email at cs.ubc.ca
Pierre Del MoralResearch Director, INRIA Bordeaux - Sud OuestVerified email at inria.fr
Gavin ShaddickProfessor of Data Science and Statistics, Department of Mathematics, University of ExeterVerified email at exeter.ac.uk
François CaronUniversity of OxfordVerified email at stats.ox.ac.uk
Nando de FreitasCIFAR & DeepMindVerified email at google.com
Max WellingCAIO CuspAI & Professor Machine Learning, University of AmsterdamVerified email at uva.nl
Yutian ChenResearch Scientist, DeepMindVerified email at google.com

Luke Bornn

Co-Founder and Chief Scientist, Zelus Analytics

Verified email at stat.harvard.edu - Homepage

Statistics Machine Learning Bayesian Statistics Spatial Statistics Monte Carlo Methods


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Pointwise: Predicting points and valuing decisions in real time with NBA optical tracking data D Cervone, A D’Amour, L Bornn, K Goldsberry 8th Annual MIT Sloan Sports Analytics Conference, 2014	223	2014
Wide Open Spaces: A statistical technique for measuring space creation in professional soccer J Fernandez, L Bornn Sloan sports analytics conference 2018, 2018	203	2018
A multiresolution stochastic process model for predicting basketball possession outcomes D Cervone, A D’Amour, L Bornn, K Goldsberry Journal of the American Statistical Association 111 (514), 585-599, 2016	202	2016
Decomposing the immeasurable sport: A deep learning expected possession value framework for soccer J Fernández, L Bornn, D Cervone 13th MIT Sloan Sports Analytics Conference 2, 2019	171	2019
Factorized point process intensities: A spatial analysis of professional basketball A Miller, L Bornn, R Adams, K Goldsberry International Conference on Machine Learning (ICML), 2014	157	2014
Characterizing the spatial structure of defensive skill in professional basketball A Franks, A Miller, L Bornn, K Goldsberry Annals of Applied Statistics 9, 94-121, 2015	148	2015
Modeling non-stationary processes through dimension expansion L Bornn, G Shaddick, JV Zidek Journal of The American Statistical Association 107, 281-289, 2012	118	2012
Structural health monitoring with autoregressive support vector machines L Bornn, CR Farrar, G Park, K Farinholt Journal of Vibration and Acoustics 131 (2), 021004, 2009	118	2009
Counterpoints: Advanced defensive metrics for NBA basketball A Franks, A Miller, L Bornn, K Goldsberry 9th Annual MIT Sloan Sports Analytics Conference, Boston, MA, 2015	103	2015
Damage detection in initially nonlinear systems L Bornn, CR Farrar, G Park International Journal of Engineering Science 48 (10), 909-920, 2010	85	2010
A framework for the fine-grained evaluation of the instantaneous expected value of soccer possessions J Fernández, L Bornn, D Cervone Machine Learning 110 (6), 1389-1427, 2021	78	2021
Vibration characteristics of vaulted masonry monuments undergoing differential support settlement S Atamturktur, L Bornn, F Hemez Engineering Structures 33, 2472-2484, 2011	76	2011
Efficient stabilization of crop yield prediction in the Canadian Prairies L Bornn, JV Zidek Agricultural and forest meteorology 152, 223-232, 2012	70	2012
The use of a single pseudo-sample in approximate Bayesian computation L Bornn, NS Pillai, A Smith, D Woodard Statistics and Computing, 1-8, 2016	65*	2016
Possession sketches: Mapping NBA strategies AC Miller, L Bornn 11th Annual MIT Sloan Sports Analytics Conference, Boston, MA, 2017	63	2017
Training load and its role in injury prevention, part 2: conceptual and methodologic pitfalls FM Impellizzeri, A McCall, P Ward, L Bornn, AJ Coutts Journal of athletic training 55 (9), 893-901, 2020	61	2020
Meta-analytics: tools for understanding the statistical properties of sports metrics AM Franks, A D’Amour, D Cervone, L Bornn Journal of Quantitative Analysis in Sports 12 (4), 151-165, 2016	59	2016
An adaptive interacting Wang-Landau algorithm for automatic density exploration L Bornn, P Jacob, P Del Moral, A Doucet Journal of Computational and Graphical Statistics 22 (3), 749-773, 2013	53	2013
Deep learning of player trajectory representations for team activity analysis N Mehrasa, Y Zhong, F Tung, L Bornn, G Mori 11th mit sloan sports analytics conference 2, 3, 2018	47	2018
Soccermap: A deep learning architecture for visually-interpretable analysis in soccer J Fernández, L Bornn Machine Learning and Knowledge Discovery in Databases. Applied Data Science …, 2021	45	2021

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