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Michael S. Albergo
Michael S. Albergo
Harvard University, Society of Fellows
Verified email at nyu.edu - Homepage
Title
Cited by
Cited by
Year
Flow-based generative models for Markov chain Monte Carlo in lattice field theory
MS Albergo, G Kanwar, PE Shanahan
Phys. Rev. D 100 (3), 2019
2632019
Building normalizing flows with stochastic interpolants
MS Albergo, E Vanden-Eijnden
arXiv preprint arXiv:2209.15571, ICLR, 2022
2372022
Equivariant flow-based sampling for lattice gauge theory
G Kanwar, MS Albergo, D Boyda, K Cranmer, DC Hackett, S Racanière, ...
Phys. Rev. Lett. 125 (12), 2020
2352020
Stochastic interpolants: A unifying framework for flows and diffusions
MS Albergo, NM Boffi, E Vanden-Eijnden
arXiv preprint arXiv:2303.08797, 2023
1882023
Normalizing flows on tori and spheres
DJ Rezende, G Papamakarios, S Racanière, MS Albergo, G Kanwar, ...
ICML 2020, 2020
1662020
Sampling using gauge equivariant flows
D Boyda, G Kanwar, S Racanière, DJ Rezende, MS Albergo, K Cranmer, ...
Physical Review D 103 (7), 074504, 2021
1632021
Sit: Exploring flow and diffusion-based generative models with scalable interpolant transformers
N Ma, M Goldstein, MS Albergo, NM Boffi, E Vanden-Eijnden, S Xie
ECCV 2024, 2024
732024
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
602021
Learnability scaling of quantum states: Restricted Boltzmann machines
D Sehayek, A Golubeva, MS Albergo, B Kulchytskyy, G Torlai, RG Melko
Physical Review B 100 (19), 195125, 2019
502019
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
422022
Search for the supersymmetric partner of the top quark in the Jets+ Emiss final state at sqrt (s)= 13 TeV
ATLAS collaboration, ATLAS Collaboration
ATLAS, Geneva, Switzerland, ATLAS-CONF-2016-077, 2016
422016
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
412021
Introduction to normalizing flows for lattice field theory
MS Albergo, D Boyda, DC Hackett, G Kanwar, K Cranmer, S Racaniere, ...
arXiv preprint arXiv:2101.08176, 2021
362021
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
312022
Aspects of scaling and scalability for flow-based sampling of lattice QCD
R Abbott, MS Albergo, A Botev, D Boyda, K Cranmer, DC Hackett, ...
The European Physical Journal A 59 (11), 257, 2023
252023
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
202022
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
182023
Stochastic interpolants with data-dependent couplings
MS Albergo, M Goldstein, NM Boffi, R Ranganath, E Vanden-Eijnden
ICML 2024 (Spotlight), 2023
172023
Introduction to normalizing flows for lattice field theory (2021)
MS Albergo, D Boyda, DC Hackett, G Kanwar, K Cranmer, S Racanière, ...
arXiv preprint arXiv:2101.08176, 0
14
Non-Hertz-Millis scaling of the antiferromagnetic quantum critical metal via scalable Hybrid Monte Carlo
P Lunts, MS Albergo, M Lindsey
Nature communications 14 (1), 2547, 2023
112023
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