Luke Bornn
Luke Bornn
Co-Founder and Chief Scientist, Zelus Analytics
Verified email at stat.harvard.edu - Homepage
Title
Cited by
Cited by
Year
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
1412014
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
1162014
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
1022016
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
892015
Modeling non-stationary processes through dimension expansion
L Bornn, G Shaddick, JV Zidek
Journal of The American Statistical Association 107, 281-289, 2012
892012
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
842009
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
652015
Wide Open Spaces: A statistical technique for measuring space creation in professional soccer
J Fernandez, L Bornn
Sloan Sports Analytics Conference 2018, 2018
622018
Damage detection in initially nonlinear systems
L Bornn, CR Farrar, G Park
International Journal of Engineering Science 48 (10), 909-920, 2010
612010
Vibration characteristics of vaulted masonry monuments undergoing differential support settlement
S Atamturktur, L Bornn, F Hemez
Engineering Structures 33, 2472-2484, 2011
59*2011
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, 2019
572019
Efficient stabilization of crop yield prediction in the Canadian Prairies
L Bornn, JV Zidek
Agricultural and forest meteorology 152, 223-232, 2012
542012
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
47*2016
Possession sketches: Mapping NBA strategies
AC Miller, L Bornn
11th Annual MIT Sloan Sports Analytics Conference, Boston, MA, 2017
352017
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
332013
An efficient computational approach for prior sensitivity analysis and cross‐validation
L Bornn, A Doucet, R Gottardo
Canadian Journal of Statistics 38 (1), 47-64, 2010
322010
The Bayesian elastic net
L Bornn, A Doucet, R Gottardo
CMS-MITACS Joint Conference, 2010
28*2010
A mixture-of-modelers approach to forecasting NCAA tournament outcomes
LH Yuan, A Liu, A Yeh, A Kaufman, A Reece, P Bull, A Franks, S Wang, ...
Journal of Quantitative Analysis in Sports 11 (1), 13-27, 2015
272015
Connecting point-level and gridded moments in the analysis of climate data
H Director, L Bornn
Journal of Climate 28 (9), 3496-3510, 2015
252015
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
212018
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