Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-08T23:05:15.774278Z
Paper Citation Record · LEDGER
As of 9 August 2026, this Paper Citation Record lists 87 of 87 outbound references and 1 inbound Pith citation observation for arXiv:2502.04246.
A citation records a reference. It does not transfer a finding from one paper to another.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-08T23:05:15.774278Z
One-hop event checks from named stored sources.
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Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-04T15:51:52.173447Z
A source-named dated measurement, never combined with another source.
Source: cited_works
87 of 87 outbound references displayed
External citation measurements
No source-named external measurement is stored.
Observation 560cb019-8a2a-4962-913a-d2546315c444 · outbound
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
Reference 1
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Observation 057eb5ca-d0f3-4382-9bcf-107d91874c73 · outbound
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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Observation 3cb8347f-1f11-48d2-842c-4694701ef0f6 · outbound
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
Reference 4
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Observation e6b226c1-3526-4249-a9ed-03c25c0fcc03 · outbound
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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Observation 0e5a8d34-92e1-4518-a540-0c455f18151a · outbound
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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Observation e0bd29ff-8145-4d6b-8ff1-8cfa06ac3891 · outbound
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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Observation 7f334779-870e-4a33-805c-d3d12b17a8f0 · outbound
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
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Observation 0e0854f1-da05-4148-8fdb-648b49bcd0fb · outbound
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
Reference 9
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Observation 66c95538-9847-4666-8018-ea12a889ba82 · outbound
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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Reference 11
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Reference 12
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Observation b04812ab-26e9-4536-83e9-bd8cc416f767 · outbound
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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Observation 33b2483c-02e5-46a1-83a5-8c840731795d · outbound
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
Reference 14
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Observation ce43b631-c521-474d-a569-93ce793a8da7 · outbound
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
Reference 15
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Observation aef52bfd-b2aa-43d6-81d3-06e0ccc64bd0 · outbound
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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Observation d77c636c-414b-4f92-a65d-5685937ab2d8 · outbound
Reference 17
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Observation 1d28a83a-250f-428a-9971-d1b88e9a2544 · outbound
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
Reference 18
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Observation c5c72651-1a65-49d4-97c0-a93563fc5b4e · outbound
Reference 19
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Observation c6276195-141b-401e-9e92-ae9835b1e0ff · outbound
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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Observation bf0c8adf-5af0-4563-980b-4c3822e3b8e5 · outbound
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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Observation 2354f1cd-88b9-4021-8928-6a12fe061f1e · outbound
Reference 22
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Observation 8a4a3b99-dd68-4987-a362-a1531fb810e8 · outbound
Reference 23
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Observation 55231c66-7a62-45e3-abae-75878fa0a342 · outbound
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
Reference 24
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Observation fa6e990a-32bc-4bac-a14b-09470f135bc1 · outbound
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
Reference 25
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Observation 3ef5f090-3761-48fc-9d95-7088f963dfe8 · outbound
Multi-fidelity emulator for large-scale 21 cm lightcone images: a few-shot transfer learning approach with generative adversarial network Unresolved cited work
Reference 26
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Observation 0663f5fa-8823-491c-bc86-a61136cce40e · outbound
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
Reference 27
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Observation 9b2e9f8b-ba9d-457d-9397-eb50815e6e89 · outbound
Multi-fidelity emulator for large-scale 21 cm lightcone images: a few-shot transfer learning approach with generative adversarial network Generative Adversarial Networks
Reference 28
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Observation cb775b73-4633-4473-a5ce-263c4ff13434 · outbound
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
Reference 29
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Observation 7624d14b-b20a-4fa3-b4f6-ae861b89d6de · outbound
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
Reference 30
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Observation 7ec6560b-9845-4c24-b4ca-a6a97bbcacfa · outbound
Multi-fidelity emulator for large-scale 21 cm lightcone images: a few-shot transfer learning approach with generative adversarial network R., Millman , K
Reference 31
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Observation de56a208-c6f7-476f-aadf-f9f3625a04e0 · outbound
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
Reference 32
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Observation c3cf785e-b3b7-4dc8-99ea-d6c29b899122 · outbound
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
Reference 33
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Observation f7d5f916-e8a6-4a99-b191-6c988c1b0a9c · outbound
Multi-fidelity emulator for large-scale 21 cm lightcone images: a few-shot transfer learning approach with generative adversarial network Unresolved cited work
Reference 34
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Observation 488f51ca-9de0-4e99-8b23-9f39307afd57 · outbound
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
Reference 35
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Observation 369764ae-e5fb-4803-9e5b-6f25f068f489 · outbound
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
Reference 36
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Observation 3e792a51-4a6a-4231-8d6f-5446e732b301 · outbound
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
Reference 37
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Observation cd5271ea-5e5b-464c-8dfb-790f74b62361 · outbound
Multi-fidelity emulator for large-scale 21 cm lightcone images: a few-shot transfer learning approach with generative adversarial network Denoising Diffusion Probabilistic Models
Reference 38
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Observation f7b6bec9-3719-4616-89b9-508ccd22fc66 · outbound
Multi-fidelity emulator for large-scale 21 cm lightcone images: a few-shot transfer learning approach with generative adversarial network Unresolved cited work
Reference 39
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Observation f9d7878c-4e8e-4884-9cb3-b66c62277d07 · outbound
Multi-fidelity emulator for large-scale 21 cm lightcone images: a few-shot transfer learning approach with generative adversarial network Unresolved cited work
Reference 40
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Observation 2ad4bb43-941b-4ac3-bd0a-09ee69e3bb1b · outbound
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
Reference 41
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Observation 029d45eb-7e61-4714-9bae-515921239a77 · outbound
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
Reference 42
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Observation 3a0a809d-d2c9-4722-b661-f559a822764c · outbound
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
Reference 44
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Observation 1bd186f3-2c3f-4dd6-818e-84e53dea81ba · outbound
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
Reference 45
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Reference 46
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Observation 63e78831-57fd-47bb-9a7f-33fe71d3ae5c · outbound
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
Reference 47
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Observation b0c9bf19-1eab-4da9-8419-5a56109867fa · outbound
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
Reference 48
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Observation f97b4cea-7e9e-462f-a5d8-b4dea21f0c7e · outbound
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
Reference 49
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Observation 5ef51eab-4056-400d-8b0a-743fd8b0700f · outbound
Multi-fidelity emulator for large-scale 21 cm lightcone images: a few-shot transfer learning approach with generative adversarial network Unresolved cited work
Reference 50
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Observation b6c45d57-3a81-4ba0-b4ad-789d8227eb41 · outbound
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
Reference 51
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Observation 815063c6-43c6-4a34-a02b-72d61aaea744 · outbound
Multi-fidelity emulator for large-scale 21 cm lightcone images: a few-shot transfer learning approach with generative adversarial network Unresolved cited work
Reference 52
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Observation 724ca717-653d-42c8-a817-13d8e1cd14b9 · outbound
Multi-fidelity emulator for large-scale 21 cm lightcone images: a few-shot transfer learning approach with generative adversarial network Unresolved cited work
Reference 53
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Observation 7824b5b7-d5a6-4162-8bb4-30e41e69d329 · outbound
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
Reference 54
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Observation 482c0176-5f67-4a99-885d-8cb186a26c36 · outbound
Reference 55
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Observation 4c67bd57-207c-44eb-acc7-a9a6b2342387 · outbound
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
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Observation 82870d7b-7ddb-4c23-a1f8-f6d743ae372d · outbound
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
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Observation 66efec5c-28be-4c3d-9799-a09acb725833 · outbound
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
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Observation cf413bab-f90e-4fb9-a2bb-f2900b766907 · outbound
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
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Observation 99d663ec-9196-44b1-bc70-95c66a707598 · outbound
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
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Observation a9652e8a-57b2-40f6-99c9-f6b36ff493d9 · outbound
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
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Observation 1df6b9dc-7298-4c8e-9ebe-ea4dc7f0c52c · outbound
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
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Observation c94cdaba-8e03-41a5-aea7-56fad5cfa25d · outbound
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
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Observation a5196358-4696-45cf-89a5-eae9b55e604f · outbound
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
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Observation 1affd50c-3c99-4648-a6ac-af495efa4096 · outbound
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
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Observation 1d04ddaa-a986-40c7-a37f-d887ec099375 · outbound
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
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Observation 97386825-46ba-48db-9327-6ffcf550b8eb · outbound
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
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Reference 70
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Observation 516b86f6-1891-43d9-b818-dbd2a70ea606 · outbound
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
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Observation b9a579f4-4f03-4faa-b82a-2196aa395f3a · outbound
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
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Observation 3dabb926-54da-41e2-8a9e-806e70cf2abc · outbound
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
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Observation c01ff2b5-6951-4d0c-a477-5bb4b594f192 · outbound
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
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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
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Observation 8b4fcacd-7edc-4b6e-a50f-3a8bfcf8b268 · outbound
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
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Observation 34f61011-4df6-4a60-9700-062643aef4f6 · outbound
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
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Observation f943c840-5987-4698-92b0-1fae9021909e · outbound
Reference 78
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Observation a53c5472-2ecf-493c-9f70-6ab18aa6d0a4 · outbound
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
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Observation b07ad527-bce0-4d50-8b40-71d2ec02b731 · outbound
Reference 80
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Observation 00d2abe5-a44a-4d36-af88-038d76729a91 · outbound
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
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Observation 2d9b5d19-33ed-4abb-9852-acf093238d97 · outbound
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
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Observation 1296a23d-f0c7-48a0-a60d-132de8436a67 · outbound
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
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