Upscaling Glasma simulations using machine learning

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Primary Data

Project Acronym Projekt Kurzbezeichnung
Glasma-ML
 
Project Title (de) Projekttitel (de)
Upscaling Glasma simulations using machine learning
 
Project Title (en) Projekttitel (en)
Upscaling Glasma simulations using machine learning
 
Consortium Coordinator Koordinator des Konsortiums
 
Principal Investigator Projektleiter_in
 

Grants

Funder/Funding Agency Fördergeber
FWF - Österr. Wissenschaftsfonds
Grant number Förderkennnummer
P 32446-N27
 

Publications

Results 1-20 of 29 (Search time: 0.005 seconds).

PreviewAuthor(s)TitleTypeIssue Date
1Holland, Kieran ; Ipp, Andreas ; Müller, David ; Wenger, Urs Fixed point actions from convolutional neural networksInproceedings Konferenzbeitrag29-Nov-2023
2Ipp, Andreas Symmetries and MLPresentation Vortrag18-Aug-2023
3Wenger, Urs ; Ipp, Andreas ; Müller, David ; Holland, Kieran Machine learning a fixed point actionPresentation Vortrag28-Jun-2023
4Ipp, Andreas ; Müller, David ; Schuh, Daniel ; Favoni, Matteo Visualizing the inner workings of L-CNNsPresentation Vortrag27-Jun-2023
5Müller, David Applications of group and gauge equivariant neural networks to problems in lattice field theoryPresentation Vortrag16-May-2023
6Aronsson, Jimmy ; Müller, David ; Schuh, Daniel Geometrical aspects of lattice gauge equivariant convolutional neural networksPreprint Preprint23-Mar-2023
7Schuh, Daniel Transverse momentum broadening in the glasma: real-time lattice simulations and the weak-field limitPresentation Vortrag6-Apr-2022
8Ipp, Andreas ; Mueller, David ; Favoni, Matteo ; Schuh, Daniel Preserving gauge invariance in neural networksKonferenzbeitrag Inproceedings 2022
9Favoni, Matteo ; Ipp, Andreas ; Müller, David I. ; Schuh, Daniel Lattice gauge equivariant convolutional neural networksArtikel Article 2022
10Bulusu, Srinath ; Favoni, Matteo ; Ipp, Andreas ; Mueller, David ; Schuh, Daniel Translational equivariance in neural networksPräsentation Presentation2021
11Ipp, Andreas ; Favoni, Matteo ; Mueller, David ; Schuh, Daniel Preserving lattice gauge equivariance in neural networksPräsentation Presentation2021
12Ipp, Andreas ; Favoni, Matteo ; Mueller, David ; Schuh, Daniel Generic Lattice gauge equivariant CNNPräsentation Presentation2021
13Ipp, Andreas ; Mueller, David Simulating the Glasma stage in heavy ion collisionsPräsentation Presentation2021
14Bulusu, Srinath ; Favoni, Matteo ; Ipp, Andreas ; Müller, David I. ; Schuh, Daniel Generalization capabilities of translationally equivariant neural networksArtikel Article 2021
15Ipp, Andreas ; Müller, David I. ; Schlichting, Soeren ; Singh, Pragya Spacetime structure of (3+1)D color fields in high energy nuclear collisionsArtikel Article 2021
16Sato, Nobuo ; Shanahan, Phiala ; Ipp, Andreas ; Cranmer, Kyle Machine Learning Round TablePräsentation Presentation2021
17Ipp, Andreas ; Mueller, David ; Schuh, Daniel Transverse momentum broadening in real-time lattice simulations of the glasmaPräsentation Presentation2021
18Favoni, Matteo ; Ipp, Andreas ; Mueller, David ; Schuh, Daniel Lattice Gauge Symmetry in Neural NetworksPräsentation Presentation2021
19Favoni, Matteo ; Ipp, Andreas ; Mueller, David ; Schuh, Daniel Implementing gauge symmetry in machine learning modelsPräsentation Presentation2021
20Bulusu, Srinath ; Favoni, Matteo ; Ipp, Andreas ; Mueller, David ; Schuh, Daniel Generalization capabilities of neural networks in lattice applicationsPräsentation Presentation2021