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Onderzoeker
Tom Vieijra
- Trefwoorden:veeldeeltjesfysica
- Disciplines:Kwantumfysica niet elders geclassificeerd, Computationele fysica, Kwantuminformatie, computatie en communicatie
Affiliaties
- Vakgroep Fysica en Sterrenkunde (Departement)
Lid
Vanaf1 sep 2018 → 25 sep 2022
Projecten
1 - 1 of 1
- Machinaal leren en sterke correlaties in complexe fysische systemenVanaf1 okt 2018 → 15 sep 2022Financiering: FWO mandaten
Publicaties
1 - 8 van 8
- Artificial neural networks and tensor networks in Variational Monte Carlo(2022)
Auteurs: Tom Vieijra
- Direct sampling of projected entangled-pair states(2021)
Auteurs: Tom Vieijra, Jutho Haegeman, Frank Verstraete, Laurens Vanderstraeten
- Optical lattice experiments at unobserved conditions with generative adversarial deep learning(2021)
Auteurs: Corneel Casert, Kyle Mills, Tom Vieijra, Jan Ryckebusch, Isaac Tamblyn
- Dynamical large deviations of two-dimensional kinetically constrained models using a neural-network state ansatz(2021)
Auteurs: Corneel Casert, Tom Vieijra, Stephen Whitelam, Isaac Tamblyn
- Many-body quantum states with exact conservation of non-Abelian and lattice symmetries through variational Monte Carlo(2021)
Auteurs: Tom Vieijra, Jannes Nys
- Restricted Boltzmann machines for quantum states with non-abelian or anyonic symmetries(2020)
Auteurs: Tom Vieijra, Corneel Casert, Jannes Nys, Wesley De Neve, Jutho Haegeman, Jan Ryckebusch, Frank Verstraete
- Isospin composition of the high-momentum fluctuations in nuclei from asymptotic momentum distributions(2019)
Auteurs: Jan Ryckebusch, Wim Cosyn, Tom Vieijra, Corneel Casert
- Interpretable machine learning for inferring the phase boundaries in a nonequilibrium system(2019)
Auteurs: Corneel Casert, Tom Vieijra, Jannes Nys, Jan Ryckebusch