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ORCIDDavid I. Müller
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2020 – today
- 2024
[j1]David I. Müller, Jimmy Aronsson, Daniel Schuh:
Geometrical aspects of lattice gauge equivariant convolutional neural networks. Trans. Mach. Learn. Res. 2024 (2024)- [i10]Kieran Holland, Andreas Ipp, David I. Müller, Urs Wenger:
Machine learning a fixed point action for SU(3) gauge theory with a gauge equivariant convolutional neural network. CoRR abs/2401.06481 (2024) - 2023
- [i9]Jimmy Aronsson, David I. Müller, Daniel Schuh:
Geometrical aspects of lattice gauge equivariant convolutional neural networks. CoRR abs/2303.11448 (2023) - [i8]Kieran Holland, Andreas Ipp
, David I. Müller, Urs Wenger:
Fixed point actions from convolutional neural networks. CoRR abs/2311.17816 (2023) - 2022
- [i7]Matteo Favoni, Andreas Ipp, David I. Müller:
Applications of Lattice Gauge Equivariant Neural Networks. CoRR abs/2212.00832 (2022) - 2021
- [i6]Srinath Bulusu, Matteo Favoni, Andreas Ipp, David I. Müller, Daniel Schuh:
Generalization capabilities of translationally equivariant neural networks. CoRR abs/2103.14686 (2021) - [i5]Matteo Favoni, Andreas Ipp, David I. Müller, Daniel Schuh:
Lattice gauge symmetry in neural networks. CoRR abs/2111.04389 (2021) - [i4]Matteo Favoni, Andreas Ipp, David I. Müller, Daniel Schuh:
Preserving gauge invariance in neural networks. CoRR abs/2112.11239 (2021) - [i3]Srinath Bulusu, Matteo Favoni, Andreas Ipp, David I. Müller, Daniel Schuh:
Generalization capabilities of neural networks in lattice applications. CoRR abs/2112.12474 (2021) - [i2]Srinath Bulusu, Matteo Favoni, Andreas Ipp, David I. Müller, Daniel Schuh:
Equivariance and generalization in neural networks. CoRR abs/2112.12493 (2021) - 2020
- [i1]Matteo Favoni, Andreas Ipp, David I. Müller, Daniel Schuh:
Lattice gauge equivariant convolutional neural networks. CoRR abs/2012.12901 (2020)
Coauthor Index
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