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| | Preview | Author(s) | Title | Type | Issue Date |
| 1 | | Schuh, Daniel ; Ipp, Andreas ; Müller, David ; Aronsson, Jimmy ; Favoni, Matteo | Global and local symmetries in neural networks | Presentation Vortrag | 27-Jun-2023 |
| 2 | | Favoni, Matteo ; Ipp, Andreas ; Schuh, Daniel ; Müller, David | Using equivariant neural networks as maps of gauge field configurations | Presentation Vortrag | 27-Jun-2023 |
| 3 | | Ipp, Andreas ; Müller, David ; Schuh, Daniel ; Favoni, Matteo | Visualizing the inner workings of L-CNNs | Presentation Vortrag | 27-Jun-2023 |
| 4 | | Favoni, Matteo ; Ipp, Andreas ; Müller, David ; Schuh, Daniel | Generation of gauge field configurations with equivariant neural networks | Presentation Vortrag | 2-Mar-2023 |
| 5 | | Favoni, Matteo ; Ipp, Andreas ; Müller, David ; Schuh, Daniel | Machine learning with gauge symmetry | Presentation Vortrag | 6-Apr-2022 |
| 6 | | Ipp, Andreas ; Mueller, David ; Favoni, Matteo ; Schuh, Daniel | Preserving gauge invariance in neural networks | Konferenzbeitrag Inproceedings  | 2022 |
| 7 | | Ipp, Andreas ; Müller, David I. ; Schuh, Daniel | On transverse momentum broadening in real-time lattice simulations of the glasma and in the weak-field limit | Konferenzbeitrag Inproceedings | 2022 |
| 8 | | Favoni, Matteo ; Ipp, Andreas ; Müller, David I. ; Schuh, Daniel | Lattice gauge equivariant convolutional neural networks | Artikel Article | 2022 |
| 9 | | Bulusu, Srinath ; Favoni, Matteo ; Ipp, Andreas ; Müller, David I. ; Schuh, Daniel | Equivariance and generalization in neural networks | Konferenzbeitrag Inproceedings | 2022 |
| 10 | | Bulusu, Srinath ; Favoni, Matteo ; Ipp, Andreas ; Mueller, David ; Schuh, Daniel | Translational equivariance in neural networks | Präsentation Presentation | 2021 |
| 11 | | Ipp, Andreas ; Favoni, Matteo ; Mueller, David ; Schuh, Daniel | Preserving lattice gauge equivariance in neural networks | Präsentation Presentation | 2021 |
| 12 | | Ipp, Andreas ; Favoni, Matteo ; Mueller, David ; Schuh, Daniel | Generic Lattice gauge equivariant CNN | Präsentation Presentation | 2021 |
| 13 | | Bulusu, Srinath ; Ipp, Andreas ; Favoni, Matteo ; Mueller, David ; Schuh, Daniel | Translational and gauge symmetry in neural networks Andreas Ipp | Präsentation Presentation | 2021 |
| 14 | | Bulusu, Srinath ; Favoni, Matteo ; Ipp, Andreas ; Müller, David I. ; Schuh, Daniel | Generalization capabilities of translationally equivariant neural networks | Artikel Article | 2021 |
| 15 | | Ipp, Andreas ; Mueller, David ; Schuh, Daniel | Transverse momentum broadening in real-time lattice simulations of the glasma | Präsentation Presentation | 2021 |
| 16 | | Favoni, Matteo ; Ipp, Andreas ; Mueller, David ; Schuh, Daniel | Lattice Gauge Symmetry in Neural Networks | Präsentation Presentation | 2021 |
| 17 | | Favoni, Matteo ; Ipp, Andreas ; Mueller, David ; Schuh, Daniel | Implementing gauge symmetry in machine learning models | Präsentation Presentation | 2021 |
| 18 | | Bulusu, Srinath ; Favoni, Matteo ; Ipp, Andreas ; Mueller, David ; Schuh, Daniel | Generalization capabilities of neural networks in lattice applications | Präsentation Presentation | 2021 |
| 19 | | Ipp, Andreas ; Mueller, David ; Schuh, Daniel | Transverse momentum broadening of jets in the weak field limit of the glasma | Präsentation Presentation | 2021 |
| 20 | | Ipp, Andreas ; Mueller, David ; Schuh, Daniel | Jet momentum broadening in real-time lattice simulations of the glasma | Präsentation Presentation | 2021 |
