Jagadeeswaran Rathinavel

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Fred J. HickernellDepartment of Applied Mathematics, Illinois Institute of TechnologyVerified email at iit.edu
Sou-Cheng (Terrya) ChoiPrincipal Data Scientist at SAS Institute Inc. and Research Associate Professor of AppliedVerified email at iit.edu
Aleksei SorokinIllinois Institute of TechnologyVerified email at hawk.iit.edu
Michael MccourtResearch & Development, DistributionalVerified email at cornell.edu
Lan JiangIllinois Institute of TechnologyVerified email at hawk.iit.edu
Lluís Antoni Jiménez RugamaPhD student at Illinois Institute of TechnologyVerified email at hawk.iit.edu
David JensenProfessor of Computer Science, University of Massachusetts AmherstVerified email at cs.umass.edu
Miguel HernanDirector, CAUSALab / Professor of Biostatistics and Epidemiology, Harvard T.H. Chan SchoolVerified email at hsph.harvard.edu
Art OwenProfessor of Statistics, Stanford UniversityVerified email at stanford.edu
Marius HofertThe University of Hong KongVerified email at hku.hk
Pierre L'EcuyerProfessor, DIRO, University of MontrealVerified email at iro.umontreal.ca
Christiane LemieuxStatistics and Actuarial Science, University of WaterlooVerified email at uwaterloo.ca
Adrian EbertPostDoc in Applied Mathematics, Johann Radon Institut (RICAM)Verified email at oeaw.ac.at
Sergei KucherenkoImperial College LondonVerified email at imperial.ac.uk
Alexander KellerNVIDIAVerified email at nvidia.com
Ilse C. F. IpsenProfessor of Mathematics, North Carolina State UniversityVerified email at ncsu.edu
Philipp HennigUniversity of TübingenVerified email at uni-tuebingen.de
T. J. SullivanUniversity of WarwickVerified email at warwick.ac.uk
Mark GirolamiUniversity of CambridgeVerified email at cam.ac.uk
Maren MahsereciAmazon ResearchVerified email at amazon.com

Jagadeeswaran Rathinavel

Illinois institute of technology

Verified email at hawk.iit.edu - Homepage

quasi-Monte Carlo Deep learning Computer Vision


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Fast automatic Bayesian cubature using lattice sampling R Jagadeeswaran, FJ Hickernell Statistics and Computing 29 (6), 1215-1229, 2019	34	2019
QMCPy: A quasi-Monte Carlo Python library (2020) SCT Choi, FJ Hickernell, R Jagadeeswaran, M McCourt, A Sorokin URL: https://github. com/QMCSoftware/QMCSoftware. DOI: https://doi. org/10 …, 0	18*
Quasi-monte carlo software SCT Choi, FJ Hickernell, R Jagadeeswaran, MJ McCourt, AG Sorokin International Conference on Monte Carlo and Quasi-Monte Carlo Methods in …, 2020	10	2020
Video content analysis system and method for transportation system LB Jordan, SV Patel, JA Mueller, J Rathinavel, R Martinez US Patent 10,392,038, 2019	9	2019
GAIL: Guaranteed Automatic Integration Library (versions 1.0–2.3. 2). MATLAB software SCT Choi, Y Ding, FJ Hickernell, L Jiang, LA Jiménez Rugama, D Li, ...	6	2021
Fast automatic Bayesian cubature using matching kernels and designs J Rathinavel Illinois Institute of Technology, 2019	5	2019
Fast automatic bayesian cubature using sobol’sampling R Jagadeeswaran, FJ Hickernell Advances in Modeling and Simulation: Festschrift for Pierre L'Ecuyer, 301-318, 2022	4	2022
GAIL: Guaranteed Automatic Integration Library (versions 1.0–2.2). MATLAB software (2013–2017) SCT Choi, Y Ding, FJ Hickernell, L Jiang, LA Jiménez Rugama, D Li, ...	3	2021
GAIL: Guaranteed Automatic Integration Library (Version 2.3. 1)[MATLAB Software], 2020 SCT Choi, Y Ding, FJ Hickernell, L Jiang, LAJ Rugama, D Li, J Rathinavel, ...	3
Guaranteed Automatic Integration Library (GAIL): An Open-Source MATLAB Library for Function Approximation, Optimization, and Integration X Tong, SCT Choi, Y Ding, FJ Hickernell, L Jiang, LAJ Rugama, ... Journal of Open Research Software 10 (1), 2022	1	2022
Fast Automatic Bayesian Cubature Using Matching Kenrels and Designs R Jagadeeswaran PhD thesis. Illinois Institute of Technology, 2019	1	2019
On Bounding and Approximating Functions of Multiple Expectations using Quasi-Monte Carlo AG Sorokin, J Rathinavel arXiv preprint arXiv:2311.07555, 2023		2023
Challenges in Developing Great Quasi-Monte Carlo Software SCT Choi, Y Ding, FJ Hickernell, J Rathinavel, AG Sorokin arXiv preprint arXiv:2311.06162, 2023		2023
Automated signal compliance monitoring and alerting system LB Jordan, B Schabell, B Weaver, P Ganesan, R Martinez, J Rathinavel, ... US Patent 11,731,672, 2023		2023
Monte Carlo and Quasi-Monte Carlo Methods: MCQMC 2020, Oxford, United Kingdom, August 10–14 A Keller Springer Nature, 2022		2022
Probabilistic Numerical Methods-From Theory to Implementation (Dagstuhl Seminar 21432) P Hennig, ICF Ipsen, M Mahsereci, T Sullivan Schloss-Dagstuhl-Leibniz Zentrum für Informatik, 2022		2022
(Quasi-) Monte Carlo Improtance Sampling with QMCPY AG Sorokin, FJ Hickernell, SCT Choi, MJ McCourt, J Rathinavel Illinois Tech Undergraduate Research Journal 1 (1), 6-6, 2021		2021
Learned from a Data Analysis Competition”.... Susan Gruber and Mark J. van der Laan 82 Comment: Causal Inference Competitions: Where Should We Aim … CJ Oates, M Girolami, MA Osborne, D Sejdinovic, FJ Hickernell, ... Statistical Science [ISSN 0883-4237 (print); ISSN 2168-8745 (online)] 34 (1), 2019		2019
Comment on" Probabilistic Integration FJ Hickernell, R Jagadeeswaran Statistical Science 34 (1), 23-28, 2019		2019
pypi i qmcpy Save F Hickernell, SCT Choi, M McCourt, J Rathinavel, A Sorokin

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