Vadim Sokolov

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Nick PolsonProfessor of Econometrics and Statistics, University of ChicagoVerified email at chicagobooth.edu
Joshua AuldPrincipal Computational Transportation Engineer, Argonne National LaboratoryVerified email at anl.gov
Dominik KarbowskiPrincipal Research Engineer, Argonne National LaboratoryVerified email at anl.gov
Biswa Nath DattaNorthern Illinois UniversityVerified email at math.niu.edu
Kuilin ZhangMichigan TechVerified email at mtu.edu
Jeffrey LarsonComputational Mathematician, Argonne National LaboratoryVerified email at anl.gov
Todd MunsonArgonne National LaboratoryVerified email at mcs.anl.gov
Sien DengProfessor of Mathematics, Northern Illinois UniversityVerified email at niu.edu
Matthew DixonAssistant Professor of Applied Math, Illinois TechVerified email at iit.edu
Aymeric RousseauArgonne National LaboratoryVerified email at anl.gov
Amgad ElgowainyArgonne National LaboratoryVerified email at anl.gov
Michael WangArgonne National LaboratoryVerified email at anl.gov
Namwook KimHanyang UniversityVerified email at hanyang.ac.kr
Noseong ParkAssistant Professor, Yonsei UniversityVerified email at yonsei.ac.kr
Jing LiuWalmart LabsVerified email at walmart.com
Yuexi WangPhD candidate, University of ChicagoVerified email at chicagobooth.edu
Huei PengRoger L. McCarthy Professor of Mechanical Engineering, Director of McityVerified email at umich.edu
Xianan HuangUniversity of MichiganVerified email at umich.edu
Sushil JajodiaUniversity Professor, BDM International Professor, and Director, Center for Secure InformationVerified email at gmu.edu
Eric JacquierBoston UniversityVerified email at bu.edu

Vadim Sokolov

George Mason University

Verified email at gmu.edu - Homepage

Particle Filtering Deep Learning Bayesian Optimization Transportation Systems


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Deep learning for short-term traffic flow prediction N Polson, V Sokolov Transportation Research Part C: Emerging Technologies 79, 1-17, 2017	574	2017
POLARIS: Agent-based modeling framework development and implementation for integrated travel demand and network and operations simulations J Auld, M Hope, H Ley, V Sokolov, B Xu, K Zhang Transportation Research Part C: Emerging Technologies 64, 101-116, 2016	123	2016
Deep learning: A Bayesian perspective NG Polson, V Sokolov Bayesian Analysis 12 (4), 1275-1304, 2017	68	2017
Analysis of the effects of connected–automated vehicle technologies on travel demand J Auld, V Sokolov, TS Stephens Transportation Research Record 2625 (1), 1-8, 2017	58	2017
An optimization technique for damped model updating with measured data satisfying quadratic orthogonality constraint BN Datta, S Deng, VO Sokolov, DR Sarkissian Mechanical Systems and Signal Processing 23 (6), 1759-1772, 2009	37	2009
Deep learning for spatio‐temporal modeling: Dynamic traffic flows and high frequency trading MF Dixon, NG Polson, VO Sokolov Applied Stochastic Models in Business and Industry 35 (3), 788-807, 2019	33	2019
Coordinated platoon routing in a metropolitan network J Larson, T Munson, V Sokolov 2016 Proceedings of the Seventh SIAM Workshop on Combinatorial Scientific …, 2016	27	2016
Bayesian analysis of traffic flow on interstate I-55: The LWR model N Polson, V Sokolov Annals of Applied Statistics 9 (4), 1864-1888, 2015	27	2015
A solution of the affine quadratic inverse eigenvalue problem BN Datta, V Sokolov Linear algebra and its applications 434 (7), 1745-1760, 2011	25	2011
GREET Model: The Greenhouse Gases, Regulated Emissions, and Energy Use in Transportation Model M Wang, R Sabbisetti, A Elgowainy, D Dieffenthaler, A Anjum, V Sokolov Chicago, USA: Argonne National Laboratory, 2014	24	2014
Quadratic inverse eigenvalue problems, active vibration control and model updating BN Datta, V Sokolov Applied and Computational Mathematics 8 (2), 170-191, 2009	21	2009
Bayesian particle tracking of traffic flows N Polson, V Sokolov IEEE Transactions on Intelligent Transportation Systems 19 (2), 345-356, 2017	17	2017
Como funciona o deep learning MA Ponti, GBP Da Costa arXiv preprint arXiv:1806.07908, 2018	16	2018
Maximization of platoon formation through centralized routing and departure time coordination V Sokolov, J Larson, T Munson, J Auld, D Karbowski Transportation Research Record 2667 (1), 10-16, 2017	16	2017
A flexible framework for developing integrated models of transportation systems using an agent-based approach V Sokolov, J Auld, M Hope Procedia Computer Science 10, 854-859, 2012	14	2012
Internet-based stated response survey for no-notice emergency evacuations J Auld, V Sokolov, A Fontes, R Bautista Transportation Letters 4 (1), 41-53, 2012	13	2012
Clusters of driving behavior from observational smartphone data J Warren, J Lipkowitz, V Sokolov IEEE Intelligent Transportation Systems Magazine 11 (3), 171-180, 2019	12*	2019
Vehicle energy management optimisation through digital maps and connectivity D Karbowski, V Sokolov, A Rousseau 22nd ITS World Congress, 5-9, 2015	12	2015
Discussion of ‘Deep learning for finance: deep portfolios’ V Sokolov Applied Stochastic Models in Business and Industry 33 (1), 16-18, 2017	8	2017
Bayesian regularization: From Tikhonov to horseshoe NG Polson, V Sokolov Wiley Interdisciplinary Reviews: Computational Statistics 11 (4), e1463, 2019	7	2019

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