Multi-fidelity emulator for large-scale 21 cm lightcone images: a few-shot transfer learning approach with generative adversarial network | Paper Citation Record

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Multi-fidelity emulator for large-scale 21 cm lightcone images: a few-shot transfer learning approach with generative adversarial network , " * write output.state after.block = add.period write newline

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Multi-fidelity emulator for large-scale 21 cm lightcone images: a few-shot transfer learning approach with generative adversarial network write newline

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This paper cites Astrophysical Constraints from the SARAS3 non-detection of the Cosmic Dawn Sky-Averaged 21-cm Signal.

Multi-fidelity emulator for large-scale 21 cm lightcone images: a few-shot transfer learning approach with generative adversarial network Astrophysical Constraints from the SARAS3 non-detection of the Cosmic Dawn Sky-Averaged 21-cm Signal

Reference 3

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This paper cites 2020, , 641, A1, 10.1051/0004-6361/201833880.

Multi-fidelity emulator for large-scale 21 cm lightcone images: a few-shot transfer learning approach with generative adversarial network 2020, , 641, A1, 10.1051/0004-6361/201833880

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Multi-fidelity emulator for large-scale 21 cm lightcone images: a few-shot transfer learning approach with generative adversarial network 2019, , 629, A115, 10.1051/0004-6361/201834975

Reference 5

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This paper cites 2019, , 10.1093/mnras/stz1960.

Multi-fidelity emulator for large-scale 21 cm lightcone images: a few-shot transfer learning approach with generative adversarial network 2019, , 10.1093/mnras/stz1960

Reference 6

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This paper cites 2020, Journal of Machine Learning Research, 21, 1.

Multi-fidelity emulator for large-scale 21 cm lightcone images: a few-shot transfer learning approach with generative adversarial network 2020, Journal of Machine Learning Research, 21, 1

Reference 7

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This paper cites Emulating cosmological multifields with generative adversarial networks.

Multi-fidelity emulator for large-scale 21 cm lightcone images: a few-shot transfer learning approach with generative adversarial network Emulating cosmological multifields with generative adversarial networks

Reference 8

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This paper cites 2024, in 29th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, Volume 2 (ASPLOS '24) (ACM), 10.1145/3620665.3640366.

Multi-fidelity emulator for large-scale 21 cm lightcone images: a few-shot transfer learning approach with generative adversarial network 2024, in 29th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, Volume 2 (ASPLOS '24) (ACM), 10.1145/3620665.3640366

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Multi-fidelity emulator for large-scale 21 cm lightcone images: a few-shot transfer learning approach with generative adversarial network Unresolved cited work

Reference 10

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This paper cites D., Rogers, A.

Multi-fidelity emulator for large-scale 21 cm lightcone images: a few-shot transfer learning approach with generative adversarial network D., Rogers, A

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Multi-fidelity emulator for large-scale 21 cm lightcone images: a few-shot transfer learning approach with generative adversarial network G., et al

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Multi-fidelity emulator for large-scale 21 cm lightcone images: a few-shot transfer learning approach with generative adversarial network 2019, , 885, 23, 10.3847/1538-4357/ab43e6

Reference 13

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This paper cites How to quantify fields or textures? A guide to the scattering transform.

Multi-fidelity emulator for large-scale 21 cm lightcone images: a few-shot transfer learning approach with generative adversarial network How to quantify fields or textures? A guide to the scattering transform

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Multi-fidelity emulator for large-scale 21 cm lightcone images: a few-shot transfer learning approach with generative adversarial network 2020, , 499, 5902, 10.1093/mnras/staa3165

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This paper cites Inferring IGM parameters from the redshifted 21-cm Power Spectrum using Artificial Neural Networks.

Multi-fidelity emulator for large-scale 21 cm lightcone images: a few-shot transfer learning approach with generative adversarial network Inferring IGM parameters from the redshifted 21-cm Power Spectrum using Artificial Neural Networks

Reference 16

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This paper cites R., Parsons, A.

Multi-fidelity emulator for large-scale 21 cm lightcone images: a few-shot transfer learning approach with generative adversarial network R., Parsons, A

Reference 17

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This paper cites 2023, in Fortieth ICML Machine Learning for Astrophysics workshop, 12.

Multi-fidelity emulator for large-scale 21 cm lightcone images: a few-shot transfer learning approach with generative adversarial network 2023, in Fortieth ICML Machine Learning for Astrophysics workshop, 12

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Multi-fidelity emulator for large-scale 21 cm lightcone images: a few-shot transfer learning approach with generative adversarial network D., et al

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This paper cites Revisiting the Intergalactic Medium Around GRB 130606A and Constraints on the Epoch of Reionization.

Multi-fidelity emulator for large-scale 21 cm lightcone images: a few-shot transfer learning approach with generative adversarial network Revisiting the Intergalactic Medium Around GRB 130606A and Constraints on the Epoch of Reionization

Reference 20

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This paper cites M., Mellema , G., Iliev , I.

Multi-fidelity emulator for large-scale 21 cm lightcone images: a few-shot transfer learning approach with generative adversarial network M., Mellema , G., Iliev , I

Reference 21

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This paper cites R., & Oh, S.

Multi-fidelity emulator for large-scale 21 cm lightcone images: a few-shot transfer learning approach with generative adversarial network R., & Oh, S

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Multi-fidelity emulator for large-scale 21 cm lightcone images: a few-shot transfer learning approach with generative adversarial network R., Oh, S

Reference 23

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Multi-fidelity emulator for large-scale 21 cm lightcone images: a few-shot transfer learning approach with generative adversarial network R., Zaldarriaga, M., & Hernquist, L

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Multi-fidelity emulator for large-scale 21 cm lightcone images: a few-shot transfer learning approach with generative adversarial network 2019, , 484, 282, 10.1093/mnras/stz010

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Multi-fidelity emulator for large-scale 21 cm lightcone images: a few-shot transfer learning approach with generative adversarial network Unresolved cited work

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Multi-fidelity emulator for large-scale 21 cm lightcone images: a few-shot transfer learning approach with generative adversarial network 2021, in APS Meeting Abstracts, Vol

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Multi-fidelity emulator for large-scale 21 cm lightcone images: a few-shot transfer learning approach with generative adversarial network Generative Adversarial Networks

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Multi-fidelity emulator for large-scale 21 cm lightcone images: a few-shot transfer learning approach with generative adversarial network 2017, Proceedings of the International Astronomical Union, 12, 18, 10.1017/s1743921317011103

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Multi-fidelity emulator for large-scale 21 cm lightcone images: a few-shot transfer learning approach with generative adversarial network Detecting the non-Gaussianity of the 21-cm signal during reionisation with the Wavelet Scattering Transform

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Multi-fidelity emulator for large-scale 21 cm lightcone images: a few-shot transfer learning approach with generative adversarial network R., Millman , K

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Multi-fidelity emulator for large-scale 21 cm lightcone images: a few-shot transfer learning approach with generative adversarial network 2020, , 494, 5761, 10.1093/mnras/staa1151

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Multi-fidelity emulator for large-scale 21 cm lightcone images: a few-shot transfer learning approach with generative adversarial network 2017, Proceedings of the International Astronomical Union, 12, 47–51, 10.1017/S1743921317010833

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Multi-fidelity emulator for large-scale 21 cm lightcone images: a few-shot transfer learning approach with generative adversarial network Unresolved cited work

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Multi-fidelity emulator for large-scale 21 cm lightcone images: a few-shot transfer learning approach with generative adversarial network 2022, , 937, 83, 10.3847/1538-4357/ac8b09

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Multi-fidelity emulator for large-scale 21 cm lightcone images: a few-shot transfer learning approach with generative adversarial network Deep Residual Learning for Image Recognition

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Multi-fidelity emulator for large-scale 21 cm lightcone images: a few-shot transfer learning approach with generative adversarial network pyC$^2$Ray: A flexible and GPU-accelerated Radiative Transfer Framework for Simulating the Cosmic Epoch of Reionization

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Multi-fidelity emulator for large-scale 21 cm lightcone images: a few-shot transfer learning approach with generative adversarial network Denoising Diffusion Probabilistic Models

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Multi-fidelity emulator for large-scale 21 cm lightcone images: a few-shot transfer learning approach with generative adversarial network Unresolved cited work

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Multi-fidelity emulator for large-scale 21 cm lightcone images: a few-shot transfer learning approach with generative adversarial network Unresolved cited work

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Multi-fidelity emulator for large-scale 21 cm lightcone images: a few-shot transfer learning approach with generative adversarial network 2023, , 958, 21, 10.3847/1538-4357/acfcb5

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Multi-fidelity emulator for large-scale 21 cm lightcone images: a few-shot transfer learning approach with generative adversarial network 2021, Experimental Astronomy, 51, 193, 10.1007/s10686-020-09697-2

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Multi-fidelity emulator for large-scale 21 cm lightcone images: a few-shot transfer learning approach with generative adversarial network 2022, , 511, 4005, 10.1093/mnras/stab3710

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Multi-fidelity emulator for large-scale 21 cm lightcone images: a few-shot transfer learning approach with generative adversarial network Training Generative Adversarial Networks with Limited Data

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Multi-fidelity emulator for large-scale 21 cm lightcone images: a few-shot transfer learning approach with generative adversarial network 2020, in Proc

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Multi-fidelity emulator for large-scale 21 cm lightcone images: a few-shot transfer learning approach with generative adversarial network 2000, Biometrika, 87, 1, 10.1093/biomet/87.1.1

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Multi-fidelity emulator for large-scale 21 cm lightcone images: a few-shot transfer learning approach with generative adversarial network 2015, in Proceedings of Advancing Astrophysics with the Square Kilometre Array PoS ( AASKA 14) (Sissa Medialab), 10.22323/1.215.0001

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Multi-fidelity emulator for large-scale 21 cm lightcone images: a few-shot transfer learning approach with generative adversarial network A population of red candidate massive galaxies ~600 Myr after the Big Bang

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Multi-fidelity emulator for large-scale 21 cm lightcone images: a few-shot transfer learning approach with generative adversarial network Unresolved cited work

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Multi-fidelity emulator for large-scale 21 cm lightcone images: a few-shot transfer learning approach with generative adversarial network Flow Matching for Generative Modeling

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Multi-fidelity emulator for large-scale 21 cm lightcone images: a few-shot transfer learning approach with generative adversarial network Unresolved cited work

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Multi-fidelity emulator for large-scale 21 cm lightcone images: a few-shot transfer learning approach with generative adversarial network Unresolved cited work

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Multi-fidelity emulator for large-scale 21 cm lightcone images: a few-shot transfer learning approach with generative adversarial network 2012, Communications on Pure and Applied Mathematics, 65, 1331, https://doi.org/10.1002/cpa.21413

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Resolution: unresolved; no resolver link, observed 2026-08-08T23:05:15.653373Z

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Observation 482c0176-5f67-4a99-885d-8cb186a26c36 · outbound

This paper cites D., Beckman, R.

Multi-fidelity emulator for large-scale 21 cm lightcone images: a few-shot transfer learning approach with generative adversarial network D., Beckman, R

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T23:05:46.037411Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 4c67bd57-207c-44eb-acc7-a9a6b2342387 · outbound

This paper cites an unresolved cited work.

Multi-fidelity emulator for large-scale 21 cm lightcone images: a few-shot transfer learning approach with generative adversarial network Unresolved cited work

Reference 56

Resolution: unresolved; no resolver link, observed 2026-08-08T23:05:15.659976Z

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Observation 82870d7b-7ddb-4c23-a1f8-f6d743ae372d · outbound

This paper cites 2024, , 683, A24, 10.1051/0004-6361/202347591.

Multi-fidelity emulator for large-scale 21 cm lightcone images: a few-shot transfer learning approach with generative adversarial network 2024, , 683, A24, 10.1051/0004-6361/202347591

Reference 57

Resolution: unresolved; no resolver link, observed 2026-08-08T23:05:15.663144Z

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Observation 66efec5c-28be-4c3d-9799-a09acb725833 · outbound

This paper cites Which Training Methods for GANs do actually Converge?.

Multi-fidelity emulator for large-scale 21 cm lightcone images: a few-shot transfer learning approach with generative adversarial network Which Training Methods for GANs do actually Converge?

Reference 58

Resolution: unresolved; no resolver link, observed 2026-08-08T23:05:15.666519Z

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Observation cf413bab-f90e-4fb9-a2bb-f2900b766907 · outbound

This paper cites 2011, , 411, 955, 10.1111/j.1365-2966.2010.17731.x.

Multi-fidelity emulator for large-scale 21 cm lightcone images: a few-shot transfer learning approach with generative adversarial network 2011, , 411, 955, 10.1111/j.1365-2966.2010.17731.x

Reference 60

Resolution: unresolved; no resolver link, observed 2026-08-08T23:05:15.673368Z

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Observation 99d663ec-9196-44b1-bc70-95c66a707598 · outbound

This paper cites Freeze the Discriminator: a Simple Baseline for Fine-Tuning GANs.

Multi-fidelity emulator for large-scale 21 cm lightcone images: a few-shot transfer learning approach with generative adversarial network Freeze the Discriminator: a Simple Baseline for Fine-Tuning GANs

Reference 61

Resolution: unresolved; no resolver link, observed 2026-08-08T23:05:15.676294Z

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Observation a9652e8a-57b2-40f6-99c9-f6b36ff493d9 · outbound

This paper cites Five parameters are all you need (in $\Lambda$CDM).

Multi-fidelity emulator for large-scale 21 cm lightcone images: a few-shot transfer learning approach with generative adversarial network Five parameters are all you need (in $\Lambda$CDM)

Reference 62

Resolution: unresolved; no resolver link, observed 2026-08-08T23:05:15.679860Z

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Observation 1df6b9dc-7298-4c8e-9ebe-ea4dc7f0c52c · outbound

This paper cites F., & Wyithe, J.

Multi-fidelity emulator for large-scale 21 cm lightcone images: a few-shot transfer learning approach with generative adversarial network F., & Wyithe, J

Reference 63

Resolution: unresolved; no resolver link, observed 2026-08-08T23:05:15.683189Z

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Observation c94cdaba-8e03-41a5-aea7-56fad5cfa25d · outbound

This paper cites G., Greig, B., Mesinger, A., et al.

Multi-fidelity emulator for large-scale 21 cm lightcone images: a few-shot transfer learning approach with generative adversarial network G., Greig, B., Mesinger, A., et al

Reference 65

Resolution: unresolved; no resolver link, observed 2026-08-08T23:05:15.689999Z

Source-reported events for the cited work

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Observation a5196358-4696-45cf-89a5-eae9b55e604f · outbound

This paper cites Schrodinger's Galaxy Candidate: Puzzlingly Luminous at $z\approx17$, or Dusty/Quenched at $z\approx5$?.

Multi-fidelity emulator for large-scale 21 cm lightcone images: a few-shot transfer learning approach with generative adversarial network Schrodinger's Galaxy Candidate: Puzzlingly Luminous at $z\approx17$, or Dusty/Quenched at $z\approx5$?

Reference 66

Resolution: unresolved; no resolver link, observed 2026-08-08T23:05:15.693226Z

Source-reported events for the cited work

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Observation 1affd50c-3c99-4648-a6ac-af495efa4096 · outbound

This paper cites 2021, , 507, 1021, 10.1093/mnras/stab2113.

Multi-fidelity emulator for large-scale 21 cm lightcone images: a few-shot transfer learning approach with generative adversarial network 2021, , 507, 1021, 10.1093/mnras/stab2113

Reference 67

Resolution: verified exact; doi, observed 2026-08-08T23:05:15.953239Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 1d04ddaa-a986-40c7-a37f-d887ec099375 · outbound

This paper cites Few-shot Image Generation via Cross-domain Correspondence.

Multi-fidelity emulator for large-scale 21 cm lightcone images: a few-shot transfer learning approach with generative adversarial network Few-shot Image Generation via Cross-domain Correspondence

Reference 68

Resolution: metadata mismatch; local_arxiv, observed 2026-08-08T23:05:27.957279Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 97386825-46ba-48db-9327-6ffcf550b8eb · outbound

This paper cites R., Liu, A., Aguirre, J.

Multi-fidelity emulator for large-scale 21 cm lightcone images: a few-shot transfer learning approach with generative adversarial network R., Liu, A., Aguirre, J

Reference 69

Resolution: unresolved; no resolver link, observed 2026-08-08T23:05:15.704160Z

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Observation c7b54367-67f6-4a3a-b535-23b834766b1e · outbound

This paper cites R., & Loeb, A.

Multi-fidelity emulator for large-scale 21 cm lightcone images: a few-shot transfer learning approach with generative adversarial network R., & Loeb, A

Reference 70

Resolution: unresolved; no resolver link, observed 2026-08-08T23:05:15.707438Z

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Observation 516b86f6-1891-43d9-b818-dbd2a70ea606 · outbound

This paper cites 1998, , 299, 1097, 10.1046/j.1365-8711.1998.01845.x.

Multi-fidelity emulator for large-scale 21 cm lightcone images: a few-shot transfer learning approach with generative adversarial network 1998, , 299, 1097, 10.1046/j.1365-8711.1998.01845.x

Reference 71

Resolution: verified exact; arxiv_id_nonexistent, observed 2026-08-08T23:05:27.942418Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation b9a579f4-4f03-4faa-b82a-2196aa395f3a · outbound

This paper cites 2017, , 468, 3869, 10.1093/mnras/stx734.

Multi-fidelity emulator for large-scale 21 cm lightcone images: a few-shot transfer learning approach with generative adversarial network 2017, , 468, 3869, 10.1093/mnras/stx734

Reference 72

Resolution: unresolved; no resolver link, observed 2026-08-08T23:05:15.713948Z

Source-reported events for the cited work

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Observation 3dabb926-54da-41e2-8a9e-806e70cf2abc · outbound

This paper cites 2024, , 527, 9977, 10.1093/mnras/stad3699.

Multi-fidelity emulator for large-scale 21 cm lightcone images: a few-shot transfer learning approach with generative adversarial network 2024, , 527, 9977, 10.1093/mnras/stad3699

Reference 73

Resolution: unresolved; no resolver link, observed 2026-08-08T23:05:15.717151Z

Source-reported events for the cited work

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Observation c01ff2b5-6951-4d0c-a477-5bb4b594f192 · outbound

This paper cites Score-Based Generative Modeling through Stochastic Differential Equations.

Multi-fidelity emulator for large-scale 21 cm lightcone images: a few-shot transfer learning approach with generative adversarial network Score-Based Generative Modeling through Stochastic Differential Equations

Reference 74

Resolution: unresolved; no resolver link, observed 2026-08-08T23:05:15.720418Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f121b7b1-de74-4ada-80f6-2ce2d0c12a31 · outbound

This paper cites syren-new: Precise formulae for the linear and nonlinear matter power spectra with massive neutrinos and dynamical dark energy.

Multi-fidelity emulator for large-scale 21 cm lightcone images: a few-shot transfer learning approach with generative adversarial network syren-new: Precise formulae for the linear and nonlinear matter power spectra with massive neutrinos and dynamical dark energy

Reference 75

Resolution: unresolved; no resolver link, observed 2026-08-08T23:05:15.724480Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8b4fcacd-7edc-4b6e-a50f-3a8bfcf8b268 · outbound

This paper cites J., Goeke, R., Bowman, J.

Multi-fidelity emulator for large-scale 21 cm lightcone images: a few-shot transfer learning approach with generative adversarial network J., Goeke, R., Bowman, J

Reference 76

Resolution: unresolved; no resolver link, observed 2026-08-08T23:05:15.727959Z

Source-reported events for the cited work

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Observation 34f61011-4df6-4a60-9700-062643aef4f6 · outbound

This paper cites an unresolved cited work.

Multi-fidelity emulator for large-scale 21 cm lightcone images: a few-shot transfer learning approach with generative adversarial network Unresolved cited work

Reference 77

Resolution: unresolved; no resolver link, observed 2026-08-08T23:05:15.731149Z

Source-reported events for the cited work

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Observation f943c840-5987-4698-92b0-1fae9021909e · outbound

This paper cites P., Wise, M.

Multi-fidelity emulator for large-scale 21 cm lightcone images: a few-shot transfer learning approach with generative adversarial network P., Wise, M

Reference 78

Resolution: unresolved; no resolver link, observed 2026-08-08T23:05:15.734472Z

Source-reported events for the cited work

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Observation a53c5472-2ecf-493c-9f70-6ab18aa6d0a4 · outbound

This paper cites The CAMELS project: public data release.

Multi-fidelity emulator for large-scale 21 cm lightcone images: a few-shot transfer learning approach with generative adversarial network The CAMELS project: public data release

Reference 79

Resolution: unresolved; no resolver link, observed 2026-08-08T23:05:15.737751Z

Source-reported events for the cited work

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Observation b07ad527-bce0-4d50-8b40-71d2ec02b731 · outbound

This paper cites H., & Cen, R.

Multi-fidelity emulator for large-scale 21 cm lightcone images: a few-shot transfer learning approach with generative adversarial network H., & Cen, R

Reference 80

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T23:05:46.027520Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 00d2abe5-a44a-4d36-af88-038d76729a91 · outbound

This paper cites Ten-parameter simulation suite for cosmological emulation beyond $\Lambda$CDM.

Multi-fidelity emulator for large-scale 21 cm lightcone images: a few-shot transfer learning approach with generative adversarial network Ten-parameter simulation suite for cosmological emulation beyond $\Lambda$CDM

Reference 81

Resolution: unresolved; no resolver link, observed 2026-08-08T23:05:15.744254Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2d9b5d19-33ed-4abb-9852-acf093238d97 · outbound

This paper cites an unresolved cited work.

Multi-fidelity emulator for large-scale 21 cm lightcone images: a few-shot transfer learning approach with generative adversarial network Unresolved cited work

Reference 82

Resolution: verified exact; doi, observed 2026-08-08T23:05:15.872012Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 1296a23d-f0c7-48a0-a60d-132de8436a67 · outbound

This paper cites 2021, , 506, 357, 10.1093/mnras/stab1718.

Multi-fidelity emulator for large-scale 21 cm lightcone images: a few-shot transfer learning approach with generative adversarial network 2021, , 506, 357, 10.1093/mnras/stab1718

Reference 83

Resolution: unresolved; no resolver link, observed 2026-08-08T23:05:15.751143Z

Source-reported events for the cited work

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Observation 2d145542-ec03-4dba-acbc-f80ce3247fd4 · outbound

This paper cites 2025, The Open Journal of Astrophysics, 8, E13, 10.33232/001c.129471.

Multi-fidelity emulator for large-scale 21 cm lightcone images: a few-shot transfer learning approach with generative adversarial network 2025, The Open Journal of Astrophysics, 8, E13, 10.33232/001c.129471

Reference 84

Resolution: verified exact; doi, observed 2026-08-08T23:05:15.854772Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation a74473fa-4e2d-44bc-b2f7-4b4ad0457d80 · outbound

This paper cites 2024, , 528, 281, 10.1093/mnras/stad3940.

Multi-fidelity emulator for large-scale 21 cm lightcone images: a few-shot transfer learning approach with generative adversarial network 2024, , 528, 281, 10.1093/mnras/stad3940

Reference 85

Resolution: unresolved; no resolver link, observed 2026-08-08T23:05:15.758096Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5369d2e3-80d8-464d-968a-4ec4dd7f64b9 · outbound

This paper cites an unresolved cited work.

Multi-fidelity emulator for large-scale 21 cm lightcone images: a few-shot transfer learning approach with generative adversarial network Unresolved cited work

Reference 86

Resolution: unresolved; no resolver link, observed 2026-08-08T23:05:15.761770Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c65655fd-f466-415a-b3dd-81515b39a889 · outbound

This paper cites an unresolved cited work.

Multi-fidelity emulator for large-scale 21 cm lightcone images: a few-shot transfer learning approach with generative adversarial network Unresolved cited work

Reference 87

Resolution: unresolved; no resolver link, observed 2026-08-08T23:05:15.764878Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e81b9200-9b2a-41e3-878b-4b6a84709e09 · outbound

This paper cites an unresolved cited work.

Multi-fidelity emulator for large-scale 21 cm lightcone images: a few-shot transfer learning approach with generative adversarial network Unresolved cited work

Reference 88

Resolution: unresolved; no resolver link, observed 2026-08-08T23:05:15.768053Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 72498e67-31a9-4ce4-abce-37397941a98e · outbound

This paper cites 2023, , 526, 1699, 10.1093/mnras/stad2778.

Multi-fidelity emulator for large-scale 21 cm lightcone images: a few-shot transfer learning approach with generative adversarial network 2023, , 526, 1699, 10.1093/mnras/stad2778

Reference 89

Resolution: unresolved; no resolver link, observed 2026-08-08T23:05:15.771187Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ca86e9e7-2cfc-404e-93ca-e9118a732e38 · outbound

This paper cites D., Bosman , S.

Multi-fidelity emulator for large-scale 21 cm lightcone images: a few-shot transfer learning approach with generative adversarial network D., Bosman , S

Reference 90

Resolution: unresolved; no resolver link, observed 2026-08-08T23:05:15.774278Z

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