Symmetry-preserving neural networks in lattice field theories | Paper Citation Record

Observation 0f5e69d0-6038-4a89-a508-0a1abadd28dc · outbound

This paper cites Generalization capabilities of translationally equivariant neural networks.

Symmetry-preserving neural networks in lattice field theories Generalization capabilities of translationally equivariant neural networks

Reference 1

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This paper cites Lattice gauge equivariant convolutional neural networks.

Symmetry-preserving neural networks in lattice field theories Lattice gauge equivariant convolutional neural networks

Reference 2

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Observation 913926da-69ec-4ed9-b7ac-05219c412ce5 · outbound

This paper cites Applications of Lattice Gauge Equivariant Neural Networks.

Symmetry-preserving neural networks in lattice field theories Applications of Lattice Gauge Equivariant Neural Networks

Reference 3

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This paper cites Weinberg, A Model of Leptons , Phys.

Symmetry-preserving neural networks in lattice field theories Weinberg, A Model of Leptons , Phys

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This paper cites Salam, Weak and Electromagnetic Interactions , Conf.

Symmetry-preserving neural networks in lattice field theories Salam, Weak and Electromagnetic Interactions , Conf

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Symmetry-preserving neural networks in lattice field theories Unresolved cited work

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Observation f067a44e-875c-4d04-986c-1d363d96e595 · outbound

This paper cites The anomalous magnetic moment of the muon in the Standard Model.

Symmetry-preserving neural networks in lattice field theories The anomalous magnetic moment of the muon in the Standard Model

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Symmetry-preserving neural networks in lattice field theories Metropolis and S

Reference 8

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Observation 56c20967-23f1-42bd-9d0f-761fabb55cb5 · outbound

This paper cites Sokal, Monte Carlo Methods in Statistical Mechanics: Foundations and New Algorithms , Springer US, Boston, MA (1997), 10.1007/978-1-4899-0319-8 6.

Symmetry-preserving neural networks in lattice field theories Sokal, Monte Carlo Methods in Statistical Mechanics: Foundations and New Algorithms , Springer US, Boston, MA (1997), 10.1007/978-1-4899-0319-8 6

Reference 9

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This paper cites Aarts, Introductory lectures on lattice QCD at nonzero baryon number, Journal of Physics: Conference Series 706 (2016) 022004.

Symmetry-preserving neural networks in lattice field theories Aarts, Introductory lectures on lattice QCD at nonzero baryon number, Journal of Physics: Conference Series 706 (2016) 022004

Reference 10

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Observation 3875f6e0-e4c9-4b0f-9f64-fc830c44b169 · outbound

This paper cites Approaches to the sign problem in lattice field theory.

Symmetry-preserving neural networks in lattice field theories Approaches to the sign problem in lattice field theory

Reference 11

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This paper cites ImageNet Large Scale Visual Recognition Challenge.

Symmetry-preserving neural networks in lattice field theories ImageNet Large Scale Visual Recognition Challenge

Reference 12

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This paper cites GPT-4 Technical Report.

Symmetry-preserving neural networks in lattice field theories GPT-4 Technical Report

Reference 13

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Observation 40b64969-1dd1-4768-8ed5-7d1c082b4878 · outbound

This paper cites Silver, T.

Symmetry-preserving neural networks in lattice field theories Silver, T

Reference 14

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This paper cites Jumper, R.

Symmetry-preserving neural networks in lattice field theories Jumper, R

Reference 15

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Symmetry-preserving neural networks in lattice field theories Unresolved cited work

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This paper cites Dubey, S.K.

Symmetry-preserving neural networks in lattice field theories Dubey, S.K

Reference 17

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This paper cites Rosenblatt, The perceptron - A perceiving and recognizing automaton, Tech.

Symmetry-preserving neural networks in lattice field theories Rosenblatt, The perceptron - A perceiving and recognizing automaton, Tech

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This paper cites Rosenblatt, The perceptron: A probabilistic model for information storage and organization in the brain.

Symmetry-preserving neural networks in lattice field theories Rosenblatt, The perceptron: A probabilistic model for information storage and organization in the brain

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This paper cites LeCun, Y.

Symmetry-preserving neural networks in lattice field theories LeCun, Y

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This paper cites An overview of gradient descent optimization algorithms.

Symmetry-preserving neural networks in lattice field theories An overview of gradient descent optimization algorithms

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This paper cites Ying, An Overview of Overfitting and its Solutions , Journal of Physics: Conference Series 1168 (2019) 022022.

Symmetry-preserving neural networks in lattice field theories Ying, An Overview of Overfitting and its Solutions , Journal of Physics: Conference Series 1168 (2019) 022022

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Observation 956af411-2724-4c82-adfe-43ea1f2ddf7f · outbound

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Symmetry-preserving neural networks in lattice field theories Cybenko, Approximation by superpositions of a sigmoidal function, Mathematics of Control, Signals and Systems 2 (1989) 303

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This paper cites The Expressive Power of Neural Networks: A View from the Width.

Symmetry-preserving neural networks in lattice field theories The Expressive Power of Neural Networks: A View from the Width

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This paper cites Carrasquilla and R.G.

Symmetry-preserving neural networks in lattice field theories Carrasquilla and R.G

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This paper cites Regressive and generative neural networks for scalar field theory.

Symmetry-preserving neural networks in lattice field theories Regressive and generative neural networks for scalar field theory

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This paper cites Continuous-mixture Autoregressive Networks for efficient variational calculation of many-body systems.

Symmetry-preserving neural networks in lattice field theories Continuous-mixture Autoregressive Networks for efficient variational calculation of many-body systems

Reference 27

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This paper cites Mapping distinct phase transitions to a neural network.

Symmetry-preserving neural networks in lattice field theories Mapping distinct phase transitions to a neural network

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This paper cites Towards Novel Insights in Lattice Field Theory with Explainable Machine Learning.

Symmetry-preserving neural networks in lattice field theories Towards Novel Insights in Lattice Field Theory with Explainable Machine Learning

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This paper cites Machine learning action parameters in lattice quantum chromodynamics.

Symmetry-preserving neural networks in lattice field theories Machine learning action parameters in lattice quantum chromodynamics

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This paper cites Estimation of Thermodynamic Observables in Lattice Field Theories with Deep Generative Models.

Symmetry-preserving neural networks in lattice field theories Estimation of Thermodynamic Observables in Lattice Field Theories with Deep Generative Models

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This paper cites Complex Paths Around The Sign Problem.

Symmetry-preserving neural networks in lattice field theories Complex Paths Around The Sign Problem

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This paper cites Towards learning optimized kernels for complex Langevin.

Symmetry-preserving neural networks in lattice field theories Towards learning optimized kernels for complex Langevin

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Symmetry-preserving neural networks in lattice field theories Lattice real-time simulations with learned optimal kernels

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This paper cites Mitigating Green's function Monte Carlo signal-to-noise problems using contour deformations.

Symmetry-preserving neural networks in lattice field theories Mitigating Green's function Monte Carlo signal-to-noise problems using contour deformations

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Symmetry-preserving neural networks in lattice field theories Machine Learning Holographic Mapping by Neural Network Renormalization Group

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Symmetry-preserving neural networks in lattice field theories Inverse Renormalization Group in Quantum Field Theory

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Observation 741c05bc-359e-46d9-a546-be10b0c355d9 · outbound

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Symmetry-preserving neural networks in lattice field theories Adding machine learning within Hamiltonians: Renormalization group transformations, symmetry breaking and restoration

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Symmetry-preserving neural networks in lattice field theories Reducing Autocorrelation Times in Lattice Simulations with Generative Adversarial Networks

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This paper cites Generative Diffusion Models for Lattice Field Theory.

Symmetry-preserving neural networks in lattice field theories Generative Diffusion Models for Lattice Field Theory

Reference 40

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Symmetry-preserving neural networks in lattice field theories Stochastic Normalizing Flows

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Symmetry-preserving neural networks in lattice field theories Stochastic normalizing flows as non-equilibrium transformations

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Observation e2b2d704-e01a-4274-96c5-cab974efb82b · outbound

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Symmetry-preserving neural networks in lattice field theories Mitigating topological freezing using out-of-equilibrium simulations

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Symmetry-preserving neural networks in lattice field theories Sampling the lattice Nambu-Goto string using Continuous Normalizing Flows

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Symmetry-preserving neural networks in lattice field theories Noether, Invariante Variationsprobleme, Nachrichten von der Gesellschaft der Wissenschaften zu G¨ ottingen, Mathematisch-Physikalische Klasse 1918 (1918) 235

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Symmetry-preserving neural networks in lattice field theories J¨ ahne,Digital Image Processing, 5th revised and extended edition , Berlin: Springer-Verlag (2002), 10.1088/0957-0233/13/9/711

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Symmetry-preserving neural networks in lattice field theories Yarotsky, Universal Approximations of Invariant Maps by Neural Networks, Constructive Approximation 55 (2022) 407

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Symmetry-preserving neural networks in lattice field theories Zhou, Universality of deep convolutional neural networks , Applied and Computational Harmonic Analysis 48 (2020) 787

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Symmetry-preserving neural networks in lattice field theories Fukushima, Neocognitron: A Self-organizing Neural Network Model for a Mechanism of Pattern Recognition Unaffected by Shift in Position, Biological Cybernetics 36 (1980) 193

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Symmetry-preserving neural networks in lattice field theories Krizhevsky, I

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Symmetry-preserving neural networks in lattice field theories Network In Network

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Symmetry-preserving neural networks in lattice field theories Unresolved cited work

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Symmetry-preserving neural networks in lattice field theories Machine Learning of Explicit Order Parameters: From the Ising Model to SU(2) Lattice Gauge Theory

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This paper cites Machine Learned Phase Transitions in a System of Anisotropic Particles on a Square Lattice.

Symmetry-preserving neural networks in lattice field theories Machine Learned Phase Transitions in a System of Anisotropic Particles on a Square Lattice

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Resolution: verified exact; local_arxiv, observed 2026-08-07T00:58:50.877389Z

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Observation 0f7eaa36-3ac2-4f3b-8e92-153e90d16656 · outbound

This paper cites Deep Reinforcement Learning Optimizes Graphene Nanopores for Efficient Desalination.

Symmetry-preserving neural networks in lattice field theories Deep Reinforcement Learning Optimizes Graphene Nanopores for Efficient Desalination

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Resolution: verified exact; local_arxiv, observed 2026-08-07T00:58:50.678385Z

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Observation eef887d7-b54f-4118-82c7-c479b1fa7d3b · outbound

This paper cites Karniadakis, I.G.

Symmetry-preserving neural networks in lattice field theories Karniadakis, I.G

Reference 56

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Observation 267ce6c6-dc3c-4786-a56f-4d3d639dd0cc · outbound

This paper cites Hamiltonian Neural Networks.

Symmetry-preserving neural networks in lattice field theories Hamiltonian Neural Networks

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This paper cites Lagrangian Neural Networks.

Symmetry-preserving neural networks in lattice field theories Lagrangian Neural Networks

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This paper cites M¨ uller,Exact conservation laws for neural network integrators of dynamical systems , Journal of Computational Physics 488 (2023) 112234.

Symmetry-preserving neural networks in lattice field theories M¨ uller,Exact conservation laws for neural network integrators of dynamical systems , Journal of Computational Physics 488 (2023) 112234

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Observation a725f05d-ba25-4c98-8ead-d870c8bd3d7b · outbound

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Symmetry-preserving neural networks in lattice field theories Group Equivariant Convolutional Networks

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Observation 5e96cee4-6250-4f62-94fd-71de449ddd36 · outbound

This paper cites Steerable CNNs.

Symmetry-preserving neural networks in lattice field theories Steerable CNNs

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Resolution: unresolved; no resolver link, observed 2026-08-07T00:58:36.289416Z

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Unavailable: canonical work link unavailable.

Observation b815964e-7a45-4cbf-a309-ba7fbd123dce · outbound

This paper cites Harmonic Networks: Deep Translation and Rotation Equivariance.

Symmetry-preserving neural networks in lattice field theories Harmonic Networks: Deep Translation and Rotation Equivariance

Reference 62

Resolution: unresolved; no resolver link, observed 2026-08-07T00:58:36.372277Z

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Observation 2bee4283-698f-438a-9090-2662b52140cd · outbound

This paper cites CubeNet: Equivariance to 3D Rotation and Translation.

Symmetry-preserving neural networks in lattice field theories CubeNet: Equivariance to 3D Rotation and Translation

Reference 63

Resolution: verified exact; local_arxiv, observed 2026-08-07T00:58:50.445101Z

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Observation 2997f42e-2144-4e73-8953-b8f96c98be92 · outbound

This paper cites A rotation-equivariant convolutional neural network model of primary visual cortex.

Symmetry-preserving neural networks in lattice field theories A rotation-equivariant convolutional neural network model of primary visual cortex

Reference 64

Resolution: verified exact; local_arxiv, observed 2026-08-07T00:58:50.181374Z

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No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation a74d1b8d-6cd3-4985-96fa-b26acc262f21 · outbound

This paper cites Rotation Equivariant CNNs for Digital Pathology.

Symmetry-preserving neural networks in lattice field theories Rotation Equivariant CNNs for Digital Pathology

Reference 65

Resolution: unresolved; no resolver link, observed 2026-08-07T00:58:36.715649Z

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Observation accbe9f4-e101-43e5-a6ff-edeed870b061 · outbound

This paper cites Roto-Translation Equivariant Convolutional Networks: Application to Histopathology Image Analysis.

Symmetry-preserving neural networks in lattice field theories Roto-Translation Equivariant Convolutional Networks: Application to Histopathology Image Analysis

Reference 66

Resolution: verified exact; local_arxiv, observed 2026-08-07T00:58:50.012050Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 2d480661-f0e8-49ae-a067-a5c033f8eeb2 · outbound

This paper cites Beyond CNNs: Exploiting Further Inherent Symmetries in Medical Images for Segmentation.

Symmetry-preserving neural networks in lattice field theories Beyond CNNs: Exploiting Further Inherent Symmetries in Medical Images for Segmentation

Reference 67

Resolution: verified exact; local_arxiv, observed 2026-08-07T00:58:49.844399Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 8af01af8-55c8-4e05-b92d-9d902b2b6a5d · outbound

This paper cites Fanaroff-Riley classification of radio galaxies using group-equivariant convolutional neural networks.

Symmetry-preserving neural networks in lattice field theories Fanaroff-Riley classification of radio galaxies using group-equivariant convolutional neural networks

Reference 68

Resolution: verified exact; local_arxiv, observed 2026-08-07T00:58:49.701517Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 29e012bb-adc1-429d-b0c5-ae014c616bab · outbound

This paper cites On the Generalization of Equivariance and Convolution in Neural Networks to the Action of Compact Groups.

Symmetry-preserving neural networks in lattice field theories On the Generalization of Equivariance and Convolution in Neural Networks to the Action of Compact Groups

Reference 69

Resolution: unresolved; no resolver link, observed 2026-08-07T00:58:37.199994Z

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Observation d30ea498-0796-497f-9872-792d4f8238ab · outbound

This paper cites Covariance in Physics and Convolutional Neural Networks.

Symmetry-preserving neural networks in lattice field theories Covariance in Physics and Convolutional Neural Networks

Reference 70

Resolution: verified exact; local_arxiv, observed 2026-08-07T00:58:49.492821Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation df285526-dd37-4060-bb1e-bcaedd286087 · outbound

This paper cites Theoretical Aspects of Group Equivariant Neural Networks.

Symmetry-preserving neural networks in lattice field theories Theoretical Aspects of Group Equivariant Neural Networks

Reference 71

Resolution: verified exact; local_arxiv, observed 2026-08-07T00:58:49.286596Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 3c89c460-bbbe-4788-9c83-15a3fa9306a4 · outbound

This paper cites Boosting Deep Neural Networks with Geometrical Prior Knowledge: A Survey.

Symmetry-preserving neural networks in lattice field theories Boosting Deep Neural Networks with Geometrical Prior Knowledge: A Survey

Reference 72

Resolution: verified exact; local_arxiv, observed 2026-08-07T00:58:49.158611Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 5bb847ee-aff7-44e7-8101-60b8b8ab65d2 · outbound

This paper cites Geometric Deep Learning and Equivariant Neural Networks.

Symmetry-preserving neural networks in lattice field theories Geometric Deep Learning and Equivariant Neural Networks

Reference 73

Resolution: verified exact; local_arxiv, observed 2026-08-07T00:58:48.945466Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation fdb902a9-dfd8-4dc9-9151-632c96718464 · outbound

This paper cites Celledoni, M.J.

Symmetry-preserving neural networks in lattice field theories Celledoni, M.J

Reference 74

Resolution: unresolved; no resolver link, observed 2026-08-07T00:58:37.830157Z

Source-reported events for the cited work

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Observation 874723e4-83ff-4f9f-b68a-3491c1525023 · outbound

This paper cites Aronsson, Homogeneous vector bundles and G-equivariant convolutional neural networks , Sampling Theory, Signal Processing, and Data Analysis 20 (2022) 10.

Symmetry-preserving neural networks in lattice field theories Aronsson, Homogeneous vector bundles and G-equivariant convolutional neural networks , Sampling Theory, Signal Processing, and Data Analysis 20 (2022) 10

Reference 75

Resolution: unresolved; no resolver link, observed 2026-08-07T00:58:37.974704Z

Source-reported events for the cited work

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Observation 2c1e9e36-9237-425c-980e-82b4ba703c4c · outbound

This paper cites Implicit Convolutional Kernels for Steerable CNNs.

Symmetry-preserving neural networks in lattice field theories Implicit Convolutional Kernels for Steerable CNNs

Reference 76

Resolution: verified exact; local_arxiv, observed 2026-08-07T00:58:48.749597Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation a9d22d46-24bb-443a-91cb-050fef95cd04 · outbound

This paper cites Hossain, S.

Symmetry-preserving neural networks in lattice field theories Hossain, S

Reference 77

Resolution: unresolved; no resolver link, observed 2026-08-07T00:58:38.202852Z

Source-reported events for the cited work

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Observation c5167c25-72ff-4665-b17b-a5b812c7f66b · outbound

This paper cites Edixhoven, A.

Symmetry-preserving neural networks in lattice field theories Edixhoven, A

Reference 78

Resolution: unresolved; no resolver link, observed 2026-08-07T00:58:38.310581Z

Source-reported events for the cited work

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Observation 4a37f704-b90f-478a-932a-a6cca03ffb7b · outbound

This paper cites Gauge Equivariant Convolutional Networks and the Icosahedral CNN.

Symmetry-preserving neural networks in lattice field theories Gauge Equivariant Convolutional Networks and the Icosahedral CNN

Reference 79

Resolution: unresolved; no resolver link, observed 2026-08-07T00:58:38.413877Z

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Observation 8fd83f4f-0234-462c-8143-2198470cd760 · outbound

This paper cites Gauge equivariant neural networks for quantum lattice gauge theories.

Symmetry-preserving neural networks in lattice field theories Gauge equivariant neural networks for quantum lattice gauge theories

Reference 80

Resolution: unresolved; no resolver link, observed 2026-08-07T00:58:38.511943Z

Source-reported events for the cited work

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Observation d5564258-a6d8-453f-b747-83a7863a8c00 · outbound

This paper cites Generalizing Convolutional Neural Networks for Equivariance to Lie Groups on Arbitrary Continuous Data.

Symmetry-preserving neural networks in lattice field theories Generalizing Convolutional Neural Networks for Equivariance to Lie Groups on Arbitrary Continuous Data

Reference 81

Resolution: unresolved; no resolver link, observed 2026-08-07T00:58:38.627300Z

Source-reported events for the cited work

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Observation 54b21998-f4ee-46f9-a468-272ce22d9648 · outbound

This paper cites Gauge covariant neural network for quarks and gluons.

Symmetry-preserving neural networks in lattice field theories Gauge covariant neural network for quarks and gluons

Reference 82

Resolution: unresolved; no resolver link, observed 2026-08-07T00:58:38.742479Z

Source-reported events for the cited work

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Observation fe9fcd2d-e8b2-4b80-b215-6e34b64cd9bf · outbound

This paper cites Geometrical aspects of lattice gauge equivariant convolutional neural networks.

Symmetry-preserving neural networks in lattice field theories Geometrical aspects of lattice gauge equivariant convolutional neural networks

Reference 83

Resolution: verified exact; local_arxiv, observed 2026-08-07T00:58:48.433396Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 2f35d0df-3e3a-4361-83b3-6b128bd7ca97 · outbound

This paper cites Gauge-equivariant neural networks as preconditioners in lattice QCD.

Symmetry-preserving neural networks in lattice field theories Gauge-equivariant neural networks as preconditioners in lattice QCD

Reference 84

Resolution: unresolved; no resolver link, observed 2026-08-07T00:58:38.966083Z

Source-reported events for the cited work

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Observation 6687f949-d2c8-45e9-9818-d912e7c8efca · outbound

This paper cites Gauge-equivariant pooling layers for preconditioners in lattice QCD.

Symmetry-preserving neural networks in lattice field theories Gauge-equivariant pooling layers for preconditioners in lattice QCD

Reference 85

Resolution: unresolved; no resolver link, observed 2026-08-07T00:58:39.066099Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ad41b40e-5761-496d-8c4e-76d2402bf201 · outbound

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

Symmetry-preserving neural networks in lattice field theories Machine learning a fixed point action for SU(3) gauge theory with a gauge equivariant convolutional neural network

Reference 86

Resolution: unresolved; no resolver link, observed 2026-08-07T00:58:39.161490Z

Source-reported events for the cited work

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Observation 61d0d7e6-eb6b-40d1-afcc-37543ed99ffe · outbound

This paper cites Self-learning Monte Carlo with equivariant Transformer.

Symmetry-preserving neural networks in lattice field theories Self-learning Monte Carlo with equivariant Transformer

Reference 87

Resolution: verified exact; local_arxiv, observed 2026-08-07T00:58:48.228936Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation e78611ab-c050-450a-83dc-983e11c069ff · outbound

This paper cites Equivariant Transformer is all you need.

Symmetry-preserving neural networks in lattice field theories Equivariant Transformer is all you need

Reference 88

Resolution: verified exact; local_arxiv, observed 2026-08-07T00:58:48.055757Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 2dccc692-8348-4d20-bb71-ebb0a971e76a · outbound

This paper cites Equivariant flow-based sampling for lattice gauge theory.

Symmetry-preserving neural networks in lattice field theories Equivariant flow-based sampling for lattice gauge theory

Reference 89

Resolution: unresolved; no resolver link, observed 2026-08-07T00:58:39.474806Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 22bbe7c8-951a-414d-83c6-4527af939172 · outbound

This paper cites Sampling using $SU(N)$ gauge equivariant flows.

Symmetry-preserving neural networks in lattice field theories Sampling using $SU(N)$ gauge equivariant flows

Reference 90

Resolution: unresolved; no resolver link, observed 2026-08-07T00:58:39.563726Z

Source-reported events for the cited work

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Observation bee0ecda-749c-45f8-bc96-c439fa356d33 · outbound

This paper cites Flow-based sampling for fermionic lattice field theories.

Symmetry-preserving neural networks in lattice field theories Flow-based sampling for fermionic lattice field theories

Reference 91

Resolution: unresolved; no resolver link, observed 2026-08-07T00:58:39.653396Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8ca5e41b-85de-490f-91ef-67269462b63e · outbound

This paper cites Abbott, M.S.

Symmetry-preserving neural networks in lattice field theories Abbott, M.S

Reference 92

Resolution: unresolved; no resolver link, observed 2026-08-07T00:58:39.778568Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f29e81e7-1bbe-4dd9-a07f-1fc3ac3c69fc · outbound

This paper cites Detecting and Mitigating Mode-Collapse for Flow-based Sampling of Lattice Field Theories.

Symmetry-preserving neural networks in lattice field theories Detecting and Mitigating Mode-Collapse for Flow-based Sampling of Lattice Field Theories

Reference 93

Resolution: unresolved; no resolver link, observed 2026-08-07T00:58:39.900674Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 484cbad4-9966-4769-9dd8-f424d441b0b8 · outbound

This paper cites Bacchio, P.

Symmetry-preserving neural networks in lattice field theories Bacchio, P

Reference 94

Resolution: unresolved; no resolver link, observed 2026-08-07T00:58:39.999839Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7e7602ed-126a-443b-8a39-8b85856f6efe · outbound

This paper cites Remarks on relativistic scalar models with chemical potential.

Symmetry-preserving neural networks in lattice field theories Remarks on relativistic scalar models with chemical potential

Reference 95

Resolution: verified exact; local_arxiv, observed 2026-08-07T00:58:47.798748Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 482383b5-09ab-4a8b-aa41-a39155afff75 · outbound

This paper cites Lattice study of the Silver Blaze phenomenon for a charged scalar phi-4 field.

Symmetry-preserving neural networks in lattice field theories Lattice study of the Silver Blaze phenomenon for a charged scalar phi-4 field

Reference 96

Resolution: unresolved; no resolver link, observed 2026-08-07T00:58:40.231523Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bd37881e-4c23-493e-809b-dbfc42af8789 · outbound

This paper cites Angulu, J.R.

Symmetry-preserving neural networks in lattice field theories Angulu, J.R

Reference 97

Resolution: unresolved; no resolver link, observed 2026-08-07T00:58:40.350656Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7e14b243-91c0-4347-b549-4bc8651d8b25 · outbound

This paper cites PyTorch: An Imperative Style, High-Performance Deep Learning Library.

Symmetry-preserving neural networks in lattice field theories PyTorch: An Imperative Style, High-Performance Deep Learning Library

Reference 98

Resolution: unresolved; no resolver link, observed 2026-08-07T00:58:40.485614Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f9b45110-26b5-4486-a192-81e633426773 · outbound

This paper cites Bozinovski, Reminder of the First Paper on Transfer Learning in Neural Networks, 1976 , Informatica (Slovenia) 44 (2020) 291.

Symmetry-preserving neural networks in lattice field theories Bozinovski, Reminder of the First Paper on Transfer Learning in Neural Networks, 1976 , Informatica (Slovenia) 44 (2020) 291

Reference 99

Resolution: unresolved; no resolver link, observed 2026-08-07T00:58:40.608054Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3a66b026-ef51-4c1b-8b54-7abbd4a02adb · outbound

This paper cites Multi-Scale Context Aggregation by Dilated Convolutions.

Symmetry-preserving neural networks in lattice field theories Multi-Scale Context Aggregation by Dilated Convolutions

Reference 100

Resolution: unresolved; no resolver link, observed 2026-08-07T00:58:40.750257Z

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