Reconstruction of spin structures from topological charge distributions via generative neural network systems | Paper Citation Record

Observation c006df2b-67eb-403f-946e-e63aebc90d15 · outbound

This paper cites Effective field theory.

Reconstruction of spin structures from topological charge distributions via generative neural network systems Effective field theory

Reference 1

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Observation e66ff11c-c59c-452a-a84d-f30d823ec43c · outbound

This paper cites Exploring topological defects in epitaxial BiFeO3 thin films.

Reconstruction of spin structures from topological charge distributions via generative neural network systems Exploring topological defects in epitaxial BiFeO3 thin films

Reference 2

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Observation 98448ed0-c989-4815-91b1-13a21c67b849 · outbound

This paper cites Skyrmion lattice in a chiral magnet.

Reconstruction of spin structures from topological charge distributions via generative neural network systems Skyrmion lattice in a chiral magnet

Reference 3

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Observation e456971e-6a6b-4959-a366-dc85f606ced1 · outbound

This paper cites Topological point defects in nematic liquid crystals.

Reconstruction of spin structures from topological charge distributions via generative neural network systems Topological point defects in nematic liquid crystals

Reference 4

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Observation 8cb9f3db-90e0-490f-82d0-7dde08824377 · outbound

This paper cites Topological defects in cholesteric liquid crystal shells.

Reconstruction of spin structures from topological charge distributions via generative neural network systems Topological defects in cholesteric liquid crystal shells

Reference 5

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Observation 6a556a0b-3a27-495d-a3ad-0787b1500142 · outbound

This paper cites Command of active matter by topological defects and patterns.

Reconstruction of spin structures from topological charge distributions via generative neural network systems Command of active matter by topological defects and patterns

Reference 6

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Observation c0b5fbcb-3155-4bb4-9460-170499bca1b0 · outbound

This paper cites Topological active matter.

Reconstruction of spin structures from topological charge distributions via generative neural network systems Topological active matter

Reference 7

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Observation 235521e1-630a-494f-89ee-7430fd01afd6 · outbound

This paper cites Perspective on uncon- ventional computing using magnetic skyrmions.

Reconstruction of spin structures from topological charge distributions via generative neural network systems Perspective on uncon- ventional computing using magnetic skyrmions

Reference 8

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Observation 60b2e4b2-7564-4af6-ba2e-f70cb219f6f6 · outbound

This paper cites Topological defects and phase transitions.

Reconstruction of spin structures from topological charge distributions via generative neural network systems Topological defects and phase transitions

Reference 9

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Observation 7e6b78c2-3f8d-427c-9884-9a63592d80ff · outbound

This paper cites Topological point defects of liquid crystals in quasi-two-dimensional geometries.

Reconstruction of spin structures from topological charge distributions via generative neural network systems Topological point defects of liquid crystals in quasi-two-dimensional geometries

Reference 10

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Observation de5f9c2a-b217-4061-bb09-27082fbd5464 · outbound

This paper cites Theory of defect motion in 2d passive and active nematic liquid crystals.

Reconstruction of spin structures from topological charge distributions via generative neural network systems Theory of defect motion in 2d passive and active nematic liquid crystals

Reference 11

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Observation 213b6315-ec48-4192-a65d-85f704206518 · outbound

This paper cites Realizing quan- titative quasiparticle modeling of skyrmion dynamics in arbitrary potentials.

Reconstruction of spin structures from topological charge distributions via generative neural network systems Realizing quan- titative quasiparticle modeling of skyrmion dynamics in arbitrary potentials

Reference 12

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Observation b15b7a97-5472-42a2-9aa9-76950e28656e · outbound

This paper cites Steady-state motion of magnetic do- mains.

Reconstruction of spin structures from topological charge distributions via generative neural network systems Steady-state motion of magnetic do- mains

Reference 13

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Observation 33b45e0f-ce4c-4a1b-9f56-e032343bd67d · outbound

This paper cites End-to-end machine learn- ing for experimental physics: using simulated data to train a neural network for object detection in video mi- croscopy.

Reconstruction of spin structures from topological charge distributions via generative neural network systems End-to-end machine learn- ing for experimental physics: using simulated data to train a neural network for object detection in video mi- croscopy

Reference 14

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Observation 33f8c282-20d1-49ca-98fc-0070582d3817 · outbound

This paper cites Machine eye for defects: Machine learning-based solution to identify and characterize topological defects in textured images of nematic materials.

Reconstruction of spin structures from topological charge distributions via generative neural network systems Machine eye for defects: Machine learning-based solution to identify and characterize topological defects in textured images of nematic materials

Reference 15

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Observation 5740556e-99bb-42da-b022-7cd78e118801 · outbound

This paper cites Machine learning vortices at the kosterlitz-thouless transition.

Reconstruction of spin structures from topological charge distributions via generative neural network systems Machine learning vortices at the kosterlitz-thouless transition

Reference 16

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Observation 8bb45f59-9ab7-4813-8120-3892c01ba071 · outbound

This paper cites Machine learn- ing topological defects of confined liquid crystals in two dimensions.

Reconstruction of spin structures from topological charge distributions via generative neural network systems Machine learn- ing topological defects of confined liquid crystals in two dimensions

Reference 17

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Observation 3ebca992-460f-42f4-a339-d3d915b0fa80 · outbound

This paper cites A machine learn- ing approach to robustly determine director fields and analyze defects in active nematics.

Reconstruction of spin structures from topological charge distributions via generative neural network systems A machine learn- ing approach to robustly determine director fields and analyze defects in active nematics

Reference 18

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Observation 8f9c92fc-a079-40d2-93db-920df05e5da1 · outbound

This paper cites A deeper look into natural sciences with physics-based and data-driven measures.

Reconstruction of spin structures from topological charge distributions via generative neural network systems A deeper look into natural sciences with physics-based and data-driven measures

Reference 19

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Observation 1d64a88a-7c1d-41b4-9cf7-15e3ac0285f7 · outbound

This paper cites Scalable computational measures for entropic de- tection of latent relations and their applications to mag- netic imaging.

Reconstruction of spin structures from topological charge distributions via generative neural network systems Scalable computational measures for entropic de- tection of latent relations and their applications to mag- netic imaging

Reference 20

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Observation a48d3469-1159-4da2-b8d9-0a0aebfb3d0e · outbound

This paper cites Towards meaningful physics from generative models.

Reconstruction of spin structures from topological charge distributions via generative neural network systems Towards meaningful physics from generative models

Reference 22

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Observation 0545eb8c-d699-4fe2-be48-716aa60ac520 · outbound

This paper cites Learning thermodynamics and topological order of the two-dimensional XY model with generative real-valued restricted boltzmann machines.

Reconstruction of spin structures from topological charge distributions via generative neural network systems Learning thermodynamics and topological order of the two-dimensional XY model with generative real-valued restricted boltzmann machines

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T23:17:13.571968Z

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Observation 2bd96828-d32b-4424-97e6-40ba95352740 · outbound

This paper cites Topological magnetic structure generation using VAE- GAN hybrid model and discriminator-driven latent sam- pling.

Reconstruction of spin structures from topological charge distributions via generative neural network systems Topological magnetic structure generation using VAE- GAN hybrid model and discriminator-driven latent sam- pling

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T23:17:13.576476Z

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Observation 141adde3-15da-47c6-840f-a15a3713e9ac · outbound

This paper cites Ordering, metastability and phase transitions in two-dimensional systems.

Reconstruction of spin structures from topological charge distributions via generative neural network systems Ordering, metastability and phase transitions in two-dimensional systems

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T23:17:13.615597Z

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Observation fb60088f-a300-4dc7-a8f0-d016f59efb00 · outbound

This paper cites Destruction of long-range order in one-dimensional and twodimensional systems having a continuous symmetry group i. classical systems.

Reconstruction of spin structures from topological charge distributions via generative neural network systems Destruction of long-range order in one-dimensional and twodimensional systems having a continuous symmetry group i. classical systems

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T23:17:13.596370Z

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Observation 625ed0de-52b6-40e3-a5dc-9ffcb1168196 · outbound

This paper cites Superfluidity and the two dimensional XY model.

Reconstruction of spin structures from topological charge distributions via generative neural network systems Superfluidity and the two dimensional XY model

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T23:17:13.646589Z

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Observation 6fc4b82f-18b6-4137-aecf-04ca5e61f604 · outbound

This paper cites an unresolved cited work.

Reconstruction of spin structures from topological charge distributions via generative neural network systems Unresolved cited work

Reference 28

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Observation 8370877e-ef20-4543-98be-8bf2a32dd7f5 · outbound

This paper cites Absence of ferromag- netism or antiferromagnetism in one- or two-dimensional isotropic heisenberg models.

Reconstruction of spin structures from topological charge distributions via generative neural network systems Absence of ferromag- netism or antiferromagnetism in one- or two-dimensional isotropic heisenberg models

Reference 29

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Observation 25b10c0d-d0a5-485a-8f03-d52365cc6d1b · outbound

This paper cites On the theory of phase transitions.

Reconstruction of spin structures from topological charge distributions via generative neural network systems On the theory of phase transitions

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T23:17:13.619226Z

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Observation 81ee3e0f-4539-4ec8-b289-e80c66c906e1 · outbound

This paper cites The two-dimensional XY model at the Berezinskii-Kosterlitz-Thouless transition.

Reconstruction of spin structures from topological charge distributions via generative neural network systems The two-dimensional XY model at the Berezinskii-Kosterlitz-Thouless transition

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T23:17:13.662545Z

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Observation bbd8f88b-05b1-49e9-bce1-a804ad979c7b · outbound

This paper cites Helicity modulus, superfluidity, and scaling in isotropic systems.

Reconstruction of spin structures from topological charge distributions via generative neural network systems Helicity modulus, superfluidity, and scaling in isotropic systems

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T23:17:13.611914Z

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Observation 0e049837-dacb-4569-9da1-fad7c58ddd70 · outbound

This paper cites Critical properties from monte carlo coarse graining and renormalization.

Reconstruction of spin structures from topological charge distributions via generative neural network systems Critical properties from monte carlo coarse graining and renormalization

Reference 33

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Observation 951a13ac-b6c3-4f81-b58b-49087605a638 · outbound

This paper cites Nakahara,Geometry, topology and physics.

Reconstruction of spin structures from topological charge distributions via generative neural network systems Nakahara,Geometry, topology and physics

Reference 34

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Observation a708db4e-8d46-4c96-8afd-207d7dda4631 · outbound

This paper cites Persistent homology—a survey.

Reconstruction of spin structures from topological charge distributions via generative neural network systems Persistent homology—a survey

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T23:17:13.641572Z

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Observation efdbde62-ce37-46c6-b3f8-c039da95d640 · outbound

This paper cites Quantita- tive analysis of phase transitions in two-dimensional XY models using persistent homology.

Reconstruction of spin structures from topological charge distributions via generative neural network systems Quantita- tive analysis of phase transitions in two-dimensional XY models using persistent homology

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T23:17:13.580694Z

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Observation 09341cd2-bb0e-44d7-b09c-f651f112fe5e · outbound

This paper cites Topological persistence and simplification.

Reconstruction of spin structures from topological charge distributions via generative neural network systems Topological persistence and simplification

Reference 37

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Observation aedad1fa-a260-4c79-8674-ee6ec84aa7e2 · outbound

This paper cites A roadmap for the computation of per- sistent homology.

Reconstruction of spin structures from topological charge distributions via generative neural network systems A roadmap for the computation of per- sistent homology

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T23:17:13.536956Z

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Observation b373aef0-ac97-4552-9c92-8b0a4e2045ae · outbound

This paper cites Persistence images: A sta- ble vector representation of persistent homology.

Reconstruction of spin structures from topological charge distributions via generative neural network systems Persistence images: A sta- ble vector representation of persistent homology

Reference 39

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Observation 120c59d4-dbe9-4276-954f-09990dd48aa7 · outbound

This paper cites Scikit-tda: Topological data anal- ysis for python.

Reconstruction of spin structures from topological charge distributions via generative neural network systems Scikit-tda: Topological data anal- ysis for python

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T23:17:13.497876Z

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Observation 41678625-44dd-48e3-802c-279621558fb0 · outbound

This paper cites Robust mor- phological measures for large scale structure in the uni- verse.

Reconstruction of spin structures from topological charge distributions via generative neural network systems Robust mor- phological measures for large scale structure in the uni- verse

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T23:17:13.485392Z

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Observation df23d224-f2cd-4550-98d5-a04867c6121c · outbound

This paper cites Neural networks fail to learn periodic functions and how to fix it.

Reconstruction of spin structures from topological charge distributions via generative neural network systems Neural networks fail to learn periodic functions and how to fix it

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T23:17:13.471426Z

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Observation 1a141972-9779-4a17-a9cc-645736c0d7da · outbound

This paper cites Pytorch: An imperative style, high- performance deep learning library.

Reconstruction of spin structures from topological charge distributions via generative neural network systems Pytorch: An imperative style, high- performance deep learning library

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T23:17:13.490040Z

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Observation a083f12b-80cd-4d20-b606-11d849dc81ce · outbound

This paper cites Wasserstein Gen- erative Adversarial Networks.

Reconstruction of spin structures from topological charge distributions via generative neural network systems Wasserstein Gen- erative Adversarial Networks

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T23:17:13.447299Z

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Observation 9c0c3f02-1778-45a7-a824-505a29346364 · outbound

This paper cites Generative adversarial nets.

Reconstruction of spin structures from topological charge distributions via generative neural network systems Generative adversarial nets

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T23:17:13.532502Z

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Observation 6eab0455-4487-443f-94ed-72aa0d6681a4 · outbound

This paper cites Mode collapse in generative adversarial networks: An overview.

Reconstruction of spin structures from topological charge distributions via generative neural network systems Mode collapse in generative adversarial networks: An overview

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T23:17:13.557654Z

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Observation c3ae202a-eb54-4f48-a7bd-c1ee2adfabc6 · outbound

This paper cites Does diffusion beat GAN in image super reso- lution?.

Reconstruction of spin structures from topological charge distributions via generative neural network systems Does diffusion beat GAN in image super reso- lution?

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T23:17:13.463294Z

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Observation f45ace15-1ddb-433f-8462-1e774bf6c2b2 · outbound

This paper cites U-net: Con- volutional networks for biomedical image segmentation.

Reconstruction of spin structures from topological charge distributions via generative neural network systems U-net: Con- volutional networks for biomedical image segmentation

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T23:17:13.650570Z

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Observation cadd32cb-2bcc-4bb5-b0bc-8d3a08a63d5e · outbound

This paper cites Arbitrary style transfer in real-time with adaptive instance normalization.

Reconstruction of spin structures from topological charge distributions via generative neural network systems Arbitrary style transfer in real-time with adaptive instance normalization

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T23:17:13.667057Z

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Observation 14d568a9-2a09-4d57-a473-b3baab943a7b · outbound

This paper cites A style-based genera- tor architecture for generative adversarial networks.

Reconstruction of spin structures from topological charge distributions via generative neural network systems A style-based genera- tor architecture for generative adversarial networks

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T23:17:13.433200Z

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Observation 392c8dc8-20c3-4e90-a48a-bfba5b86ae1c · outbound

This paper cites Rectified linear units im- prove restricted boltzmann machines.

Reconstruction of spin structures from topological charge distributions via generative neural network systems Rectified linear units im- prove restricted boltzmann machines

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T23:17:13.424633Z

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Observation 69ccc87a-6982-4208-acf8-0a3f895ba0e0 · outbound

This paper cites Rectifier nonlinearities improve neural net- work acoustic models.

Reconstruction of spin structures from topological charge distributions via generative neural network systems Rectifier nonlinearities improve neural net- work acoustic models

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T23:17:13.557020Z

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Observation 75bc6d90-591f-4f6a-b6d9-0a18ea9e3f90 · outbound

This paper cites Deconvolution and checkerboard artifacts.

Reconstruction of spin structures from topological charge distributions via generative neural network systems Deconvolution and checkerboard artifacts

Reference 53

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This paper cites Generative adversarial networks.

Reconstruction of spin structures from topological charge distributions via generative neural network systems Generative adversarial networks

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T23:17:13.559747Z

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This paper cites On a space of completely additive functions.

Reconstruction of spin structures from topological charge distributions via generative neural network systems On a space of completely additive functions

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T23:17:13.658997Z

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This paper cites On information and sufficiency.

Reconstruction of spin structures from topological charge distributions via generative neural network systems On information and sufficiency

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T23:17:13.506644Z

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This paper cites Villani,Topics in Optimal Transportation.

Reconstruction of spin structures from topological charge distributions via generative neural network systems Villani,Topics in Optimal Transportation

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T23:17:13.576957Z

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This paper cites Improved training of Wasserstein GANs.

Reconstruction of spin structures from topological charge distributions via generative neural network systems Improved training of Wasserstein GANs

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T23:17:13.481451Z

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Observation 51d414da-478f-4b5c-8259-e1eb2fc6d71b · outbound

This paper cites Evaluation of mode collapse in generative 1 adversarial networks.

Reconstruction of spin structures from topological charge distributions via generative neural network systems Evaluation of mode collapse in generative 1 adversarial networks

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T23:17:13.551136Z

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This paper cites Inception-v4, inception-resnet and the impact of resid- ual connections on learning.

Reconstruction of spin structures from topological charge distributions via generative neural network systems Inception-v4, inception-resnet and the impact of resid- ual connections on learning

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T23:17:13.470664Z

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Observation 523195c9-14ee-47ca-9a62-c6e714201c04 · outbound

This paper cites Deep resid- ual learning for image recognition.

Reconstruction of spin structures from topological charge distributions via generative neural network systems Deep resid- ual learning for image recognition

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T23:17:13.634333Z

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This paper cites This deliberate choice allows the network to robustly learn and resolve physically relevant but sta- tistically uncommon configurations.

Reconstruction of spin structures from topological charge distributions via generative neural network systems This deliberate choice allows the network to robustly learn and resolve physically relevant but sta- tistically uncommon configurations

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T23:17:13.455332Z

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Observation 1d97a68d-dfe8-4f0a-b41b-251344071e44 · outbound

This paper cites Adam: A method for stochas- tic optimization.

Reconstruction of spin structures from topological charge distributions via generative neural network systems Adam: A method for stochas- tic optimization

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T23:17:13.626907Z

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Observation 2b36f839-ce05-45b7-8664-cc45a20d7b22 · outbound

This paper cites Watch your up- convolution: CNN based generative deep neural networks are failing to reproduce spectral distributions.

Reconstruction of spin structures from topological charge distributions via generative neural network systems Watch your up- convolution: CNN based generative deep neural networks are failing to reproduce spectral distributions

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T23:17:13.426075Z

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Observation 1bc281c7-f10d-49c0-8bd1-167b9c9cb691 · outbound

This paper cites Spectral distribution aware im- age generation.

Reconstruction of spin structures from topological charge distributions via generative neural network systems Spectral distribution aware im- age generation

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T23:17:13.637674Z

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