Andreas Ipp

Andreas Ipp

Technische Universität Wien

H-index: 18

Europe-Austria

About Andreas Ipp

Andreas Ipp, With an exceptional h-index of 18 and a recent h-index of 12 (since 2020), a distinguished researcher at Technische Universität Wien, specializes in the field of Theoretical Physics, Quantum Field Theory, High Energy Physics.

His recent articles reflect a diverse array of research interests and contributions to the field:

Fixed point actions from convolutional neural networks

Energy-momentum tensor of the dilute (3+ 1) D Glasma

Machine learning a fixed point action for SU (3) gauge theory with a gauge equivariant convolutional neural network

Using equivariant neural networks as maps of gauge field configurations

Generation of gauge field configurations with equivariant neural networks

Global and local symmetries in neural networks

3+ 1D energy-momentum tensor of the dilute Glasma

Symmetries and ML

Andreas Ipp Information

University

Position

___

Citations(all)

939

Citations(since 2020)

361

Cited By

695

hIndex(all)

18

hIndex(since 2020)

12

i10Index(all)

24

i10Index(since 2020)

14

Email

University Profile Page

Technische Universität Wien

Google Scholar

View Google Scholar Profile

Andreas Ipp Skills & Research Interests

Theoretical Physics

Quantum Field Theory

High Energy Physics

Top articles of Andreas Ipp

Title

Journal

Author(s)

Publication Date

Fixed point actions from convolutional neural networks

PoS LATTICE2023 (2024) 038

Urs Wenger

K Holland

A Ipp

DI Müller

2024

Energy-momentum tensor of the dilute (3+ 1) D Glasma

arXiv preprint arXiv:2401.10320

Andreas Ipp

Markus Leuthner

David I Müller

Sören Schlichting

Kayran Schmidt

...

2024/1/18

Machine learning a fixed point action for SU (3) gauge theory with a gauge equivariant convolutional neural network

arXiv preprint arXiv:2401.06481

Kieran Holland

Andreas Ipp

David I Müller

Urs Wenger

2024/1/12

Using equivariant neural networks as maps of gauge field configurations

Matteo Favoni

Andreas Ipp

Daniel Schuh

David Müller

2023/6/27

Generation of gauge field configurations with equivariant neural networks

Matteo Favoni

Andreas Ipp

David Müller

Daniel Schuh

2023/3/2

Global and local symmetries in neural networks

Daniel Schuh

Andreas Ipp

David Müller

Jimmy Aronsson

Matteo Favoni

2023/6/27

3+ 1D energy-momentum tensor of the dilute Glasma

Markus Leuthner

David Müller

Andreas Ipp

Sören Schlichting

Pragya Singh

2023

Symmetries and ML

Andreas Ipp

2023/8/18

Simulating heavy quarks and jets in the Glasma

Dana Avramescu

Virgil Băran

Vicenzo Greco

Andreas Ipp

David Müller

...

2023/6/20

Heavy quark and jet transport coefficients in the Glasma early stage of heavy-ion collisions

arXiv preprint arXiv:2307.07999

Dana Avramescu

Virgil Băran

Vincenzo Greco

Andreas Ipp

David Müller

...

2023/7/16

3+ 1D observables in the dilute Glasma

Markus Leuthner

Andreas Ipp

David Müller

Pragya Singh

Sören Schlichting

2023/6/19

Machine learning a fixed point action

Urs Wenger

Andreas Ipp

David Müller

Kieran Holland

2023/6/28

Visualizing the inner workings of L-CNNs

Andreas Ipp

David Müller

Daniel Schuh

Matteo Favoni

2023/6/27

Simulating jets and heavy quarks in the glasma using the colored particle-in-cell method

Physical Review D

Dana Avramescu

Virgil Băran

Vincenzo Greco

Andreas Ipp

David Müller

...

2023/6/15

Studying the 3+ 1D structure of the Glasma using the weak field approximation

EPJ Web of Conferences

Andreas Ipp

Markus Leuthner

David I Müller

Soeren Schlichting

Pragya Singh

2022

Machine learning with gauge symmetry

Matteo Favoni

Andreas Ipp

David Müller

Daniel Schuh

2022/4/6

Generalization capabilities of neural networks in lattice applications

arXiv preprint arXiv:2112.12474

Srinath Bulusu

Matteo Favoni

Andreas Ipp

David I Müller

Daniel Schuh

2021/12/23

Space-time structure of 3+ 1D color fields in heavy-ion collisions

David Müller

Andreas Ipp

Soeren Schlichting

Pragya Singh

2022/4/6

Equivariance and generalization in neural networks

EPJ Web of Conferences

Srinath Bulusu

Matteo Favoni

Andreas Ipp

David I Müller

Daniel Schuh

2022

Lattice gauge equivariant convolutional neural networks

Physical Review Letters

Matteo Favoni

Andreas Ipp

David I Müller

Daniel Schuh

2022/1/20

See List of Professors in Andreas Ipp University(Technische Universität Wien)

Co-Authors

H-index: 70
Michael Strickland

Michael Strickland

Kent State University

H-index: 49
Anton Rebhan

Anton Rebhan

Technische Universität Wien

H-index: 45
Ivona Brandic

Ivona Brandic

Technische Universität Wien

H-index: 39
Aleksi Vuorinen

Aleksi Vuorinen

Helsingin yliopisto

H-index: 31
Nicolás Wschebor

Nicolás Wschebor

Universidad de la República

H-index: 13
Peter Somkuti

Peter Somkuti

Colorado State University

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