Gurtej Kanwar

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Coauteurs

Phiala ShanahanMassachusetts Institute of TechnologyAdresse e-mail validée de mit.edu
Michael S. AlbergoHarvard University, Society of FellowsAdresse e-mail validée de nyu.edu
Daniel HackettPostdoc, FermilabAdresse e-mail validée de fnal.gov
Denis L. BoydaIAIFI Fellow, MITAdresse e-mail validée de mit.edu
Kyle CranmerUniversity of Wisconsin-MadisonAdresse e-mail validée de wisc.edu
Danilo J. RezendeDirector at DeepMindAdresse e-mail validée de google.com
Sébastien RacanièreResearch Scientist, DeepMindAdresse e-mail validée de google.com
Julian M. UrbanPostdoc, MITAdresse e-mail validée de mit.edu
William DetmoldAssociate Professor, Massachusetts Institute of TechnologyAdresse e-mail validée de mit.edu
Fernando Romero-LópezPostdoc at MITAdresse e-mail validée de mit.edu
George PapamakariosGoogle DeepMindAdresse e-mail validée de google.com
Aleksandar BotevGoogle DeepmindAdresse e-mail validée de google.com
Neill C. WarringtonUniversity of Maryland, College ParkAdresse e-mail validée de terpmail.umd.edu
Ali RazaviGoogle DeepMindAdresse e-mail validée de google.com
Alexander G. D. G. MatthewsDeepMindAdresse e-mail validée de google.com
Simone BacchioCaSToRC, The Cyprus InstituteAdresse e-mail validée de cyi.ac.cy
Constantia AlexandrouUniversity of Cyprus and The Cyprus InstituteAdresse e-mail validée de ucy.ac.cy
Kyriakos HadjiyiannakouThe Cyprus InstituteAdresse e-mail validée de cyi.ac.cy
Jacob FinkenrathPost-Doc, Bergische Universitaet WuppertalAdresse e-mail validée de uni-wuppertal.de
Carsten UrbachProfessor für Physik, Universität BonnAdresse e-mail validée de hiskp.uni-bonn.de

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Gurtej Kanwar

University of Edinburgh

Adresse e-mail validée de ed.ac.uk

Particle Physics Lattice QCD Artificial Intelligence


Titre Trier par citations Trier par année Trier par titre	Citée par Citée par	Année
Flow-based generative models for Markov chain Monte Carlo in lattice field theory MS Albergo, G Kanwar, PE Shanahan Physical Review D 100 (3), 034515, 2019	257	2019
Equivariant flow-based sampling for lattice gauge theory G Kanwar, MS Albergo, D Boyda, K Cranmer, DC Hackett, S Racaniere, ... Physical Review Letters 125 (12), 121601, 2020	232	2020
Sampling using gauge equivariant flows D Boyda, G Kanwar, S Racanière, DJ Rezende, MS Albergo, K Cranmer, ... Physical Review D 103 (7), 074504, 2021	161	2021
Normalizing flows on tori and spheres DJ Rezende, G Papamakarios, S Racaniere, M Albergo, G Kanwar, ... International Conference on Machine Learning, 8083-8092, 2020	161	2020
Simit: A language for physical simulation F Kjolstad, S Kamil, J Ragan-Kelley, DIW Levin, S Sueda, D Chen, ... ACM Transactions on Graphics (TOG) 35 (2), 1-21, 2016	74	2016
Flow-based sampling for fermionic lattice field theories MS Albergo, G Kanwar, S Racanière, DJ Rezende, JM Urban, D Boyda, ... Physical Review D 104 (11), 114507, 2021	58	2021
Introduction to normalizing flows for lattice field theory MS Albergo, D Boyda, DC Hackett, G Kanwar, K Cranmer, S Racanière, ... arXiv preprint arXiv:2101.08176, 2021	48	2021
Gauge-equivariant flow models for sampling in lattice field theories with pseudofermions R Abbott, MS Albergo, D Boyda, K Cranmer, DC Hackett, G Kanwar, ... Physical Review D 106 (7), 074506, 2022	40	2022
Flow-based sampling for multimodal distributions in lattice field theory DC Hackett, CC Hsieh, MS Albergo, D Boyda, JW Chen, KF Chen, ... arXiv preprint arXiv:2107.00734, 2021	40	2021
Path integral contour deformations for observables in gauge theory W Detmold, G Kanwar, H Lamm, ML Wagman, NC Warrington Physical Review D 103 (9), 094517, 2021	39	2021
Path integral contour deformations for noisy observables W Detmold, G Kanwar, ML Wagman, NC Warrington Physical Review D 102 (1), 014514, 2020	31	2020
Flow-based sampling in the lattice Schwinger model at criticality MS Albergo, D Boyda, K Cranmer, DC Hackett, G Kanwar, S Racanière, ... Physical Review D 106 (1), 014514, 2022	30	2022
Applications of flow models to the generation of correlated lattice QCD ensembles R Abbott, A Botev, D Boyda, DC Hackett, G Kanwar, S Racanière, ... Physical Review D 109 (9), 094514, 2024	29	2024
Advances in machine-learning-based sampling motivated by lattice quantum chromodynamics K Cranmer, G Kanwar, S Racanière, DJ Rezende, PE Shanahan Nature Reviews Physics, 1-10, 2023	26	2023
Sampling QCD field configurations with gauge-equivariant flow models R Abbott, MS Albergo, A Botev, D Boyda, K Cranmer, DC Hackett, ... arXiv preprint arXiv:2208.03832, 2022	20	2022
Normalizing flows for lattice gauge theory in arbitrary space-time dimension R Abbott, MS Albergo, A Botev, D Boyda, K Cranmer, DC Hackett, ... arXiv preprint arXiv:2305.02402, 2023	18	2023
Real-time lattice gauge theory actions: Unitarity, convergence, and path integral contour deformations G Kanwar, ML Wagman Physical Review D 104 (1), 014513, 2021	18	2021
Phase unwrapping and one-dimensional sign problems W Detmold, G Kanwar, ML Wagman Physical Review D 98 (7), 074511, 2018	18	2018
transition form factor and the hadronic light-by-light -pole contribution to the muon from lattice QCD C Alexandrou, S Bacchio, S Burri, J Finkenrath, A Gasbarro, ... Physical Review D 108 (5), 054509, 2023	11	2023
Machine learning and variational algorithms for lattice field theory G Kanwar Massachusetts Institute of Technology, 2021	11	2021

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