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Paper Citation Record · LEDGER

Optical Physics-Based Generative Models

As of 9 August 2026, this Paper Citation Record lists 47 of 47 outbound references and 1 inbound Pith citation observation for arXiv:2506.04357.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2506.04357 v1

Coverage vector

measured 47 of 47 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T10:52:24.737912Z

measured 48 of 48 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T19:32:18.608360Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: pith, observed 2026-08-06T19:32:18.815179Z

Reference resolution

47 of 47 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation f92883b4-b716-4f79-b540-2d6486402db1 · outbound

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

Optical Physics-Based Generative Models A style-based generator architecture for generative adversarial networks

Reference 1

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Unavailable: canonical work link unavailable.

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Observation 04a6310d-7abd-4346-aed8-1ef67b291462 · outbound

This paper cites TACNET: Temporal Audio Source Counting Network.

Optical Physics-Based Generative Models TACNET: Temporal Audio Source Counting Network

Reference 2

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source=pdf_text observed=2026-08-07T10:52:24.522332Z digest=sha256:c8f8f229600acdd5615d52b34f16519ccf7063392120291276511a1620f19c65

Observation 10500176-1f29-499d-b7a5-9b053a456c62 · outbound

This paper cites Language models are few-shot learners.Advances in Neural Information Processing Systems, 33:1877–1901, 2020.

Optical Physics-Based Generative Models Language models are few-shot learners.Advances in Neural Information Processing Systems, 33:1877–1901, 2020

Reference 3

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source=pdf_text observed=2026-08-07T10:52:24.526666Z digest=sha256:75649479b6af482598523cf28c6d2f44a2e21fe6cd8be412e1bb69e995e7a50c

Observation 9f6040e2-cb8f-499b-ade7-d8450ac524d5 · outbound

This paper cites Highly accurate protein structure prediction with alphafold.Nature, 596(7873):583–589, 2021.

Optical Physics-Based Generative Models Highly accurate protein structure prediction with alphafold.Nature, 596(7873):583–589, 2021

Reference 4

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source=pdf_text observed=2026-08-07T10:52:24.530947Z digest=sha256:28064f63b9de27aa6c6b64e3de1fc780b62abe8d18b562bd6c1c5ea8692517fc

Observation f0761866-78e6-4b68-9425-192cbbc00c9b · outbound

This paper cites Learning to simulate complex physics with graph networks.

Optical Physics-Based Generative Models Learning to simulate complex physics with graph networks

Reference 5

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raw_fallback, observed 2026-08-07T10:52:25.487066Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 326790d8-3cf7-46b8-9326-6ebce15d9077 · outbound

This paper cites Dynamic control of spontaneous emission using magnetized insb higher-order- mode antennas.Journal of Physics: Photonics, 6(3):035011, 2024.

Optical Physics-Based Generative Models Dynamic control of spontaneous emission using magnetized insb higher-order- mode antennas.Journal of Physics: Photonics, 6(3):035011, 2024

Reference 6

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raw_fallback, observed 2026-08-07T10:52:25.469299Z

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T10:52:24.539063Z digest=sha256:5d129ff7fb52f179843c01b938ae83926d63bdbe132d038d3ad3b51e3edd7c55

Observation 2d5e5454-0e5e-4e5b-ae57-111d680c1408 · outbound

This paper cites Deep unsupervised learning using nonequilibrium thermodynamics.

Optical Physics-Based Generative Models Deep unsupervised learning using nonequilibrium thermodynamics

Reference 7

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raw_fallback, observed 2026-08-07T10:52:25.453765Z

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 18532e7f-5019-446f-a558-74d3d8ac3c62 · outbound

This paper cites Denoising diffusion probabilistic models.Advances in Neural Information Processing Systems, 33:6840–6851, 2020.

Optical Physics-Based Generative Models Denoising diffusion probabilistic models.Advances in Neural Information Processing Systems, 33:6840–6851, 2020

Reference 8

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Observation c07944b5-6e81-4195-9f0a-6aa7245861c9 · outbound

This paper cites Poisson Flow Generative Models.

Optical Physics-Based Generative Models Poisson Flow Generative Models

Reference 10

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source=pdf_text observed=2026-08-07T10:52:24.557444Z digest=sha256:41b2482519883b4c6eefbc5d8a1d58cc2a10c7a133d546c09f0803102afda37d

Observation 816dd508-91cc-4e28-b11f-5103e691e5bd · outbound

This paper cites Generative adversarial nets.Advances in Neural Information Processing Systems, 27:2672– 2680, 2014.

Optical Physics-Based Generative Models Generative adversarial nets.Advances in Neural Information Processing Systems, 27:2672– 2680, 2014

Reference 11

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raw_fallback, observed 2026-08-07T10:52:25.425431Z

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 28a191ac-edcf-4fc6-8f61-79e5456e0b88 · outbound

This paper cites Auto-Encoding Variational Bayes.

Optical Physics-Based Generative Models Auto-Encoding Variational Bayes

Reference 12

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Observation b13febe8-4267-410e-9b5f-e9c4629b202d · outbound

This paper cites GenPhys: From Physical Processes to Generative Models.

Optical Physics-Based Generative Models GenPhys: From Physical Processes to Generative Models

Reference 13

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Observation e4f5f655-e510-4e83-81fb-31d587e7be47 · outbound

This paper cites Deep learning meets nanophotonics: A generalized accurate predictor for near fields and far fields of arbitrary 3d nanostructures.Nano Letters, 20(1):329–338, 2022.

Optical Physics-Based Generative Models Deep learning meets nanophotonics: A generalized accurate predictor for near fields and far fields of arbitrary 3d nanostructures.Nano Letters, 20(1):329–338, 2022

Reference 14

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raw_fallback, observed 2026-08-07T10:52:25.409121Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 96b09caa-2fcc-491c-bbdf-4bf64f1944ee · outbound

This paper cites Free-space optical spiking neural network.PloS one, 19(12):e0313547, 2024.

Optical Physics-Based Generative Models Free-space optical spiking neural network.PloS one, 19(12):e0313547, 2024

Reference 15

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raw_fallback, observed 2026-08-07T10:52:25.393190Z

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 2f4b07f7-4df3-4b84-a2b3-f5f3f9b2c46b · outbound

This paper cites Nontrapping Tunable Topological Photonic Memory.

Optical Physics-Based Generative Models Nontrapping Tunable Topological Photonic Memory

Reference 16

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Observation 90f26abd-75b1-4585-8065-72731133f625 · outbound

This paper cites Training Large-Scale Optical Neural Networks with Two-Pass Forward Propagation.

Optical Physics-Based Generative Models Training Large-Scale Optical Neural Networks with Two-Pass Forward Propagation

Reference 17

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Observation c472891f-d9e4-46fb-ae23-0cb93c0d6b51 · outbound

This paper cites All-Optical Doubly Resonant Cavities for ReLU Function in Nanophotonic Deep Learning.

Optical Physics-Based Generative Models All-Optical Doubly Resonant Cavities for ReLU Function in Nanophotonic Deep Learning

Reference 18

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local_arxiv, observed 2026-08-07T10:52:24.933906Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 96914d8c-7b9e-4b7e-9229-d981e874c484 · outbound

This paper cites Optical physics based generative models.

Optical Physics-Based Generative Models Optical physics based generative models

Reference 19

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raw_fallback, observed 2026-08-07T10:52:25.374112Z

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 1b009995-c3c6-4dae-a253-81c284dfdeae · outbound

This paper cites Unbalanced minibatch Optimal Transport; applications to Domain Adaptation.

Optical Physics-Based Generative Models Unbalanced minibatch Optimal Transport; applications to Domain Adaptation

Reference 20

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verified exact
local_arxiv, observed 2026-08-07T10:52:24.913140Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 7f677818-6c82-46be-8ee9-4bab856a72e9 · outbound

This paper cites Unbalanced Sobolev Descent.

Optical Physics-Based Generative Models Unbalanced Sobolev Descent

Reference 21

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verified exact
local_arxiv, observed 2026-08-07T10:52:24.890293Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 8089b0ae-c6c8-47aa-bc7f-ce26c2d108cb · outbound

This paper cites Accelerating Langevin Sampling with Birth-death.

Optical Physics-Based Generative Models Accelerating Langevin Sampling with Birth-death

Reference 22

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Observation 0bc8db6f-7f6b-4e0b-80f9-2aa64cbc765d · outbound

This paper cites Cambridge University Press, 2016.

Optical Physics-Based Generative Models Cambridge University Press, 2016

Reference 23

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raw_fallback, observed 2026-08-07T10:52:25.356782Z

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Observation 1b1f5d81-f434-4b9b-925e-c12666b5edc2 · outbound

This paper cites Cambridge University Press, 7 edition, 2013.

Optical Physics-Based Generative Models Cambridge University Press, 7 edition, 2013

Reference 24

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raw_fallback, observed 2026-08-07T10:52:25.339444Z

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 17f26080-151d-4781-8b25-a351d07046c0 · outbound

This paper cites Green’s function for the lossy wave equation.Revista Brasileira de Ensino de Física, 30:1302.1–1302.5, 2008.

Optical Physics-Based Generative Models Green’s function for the lossy wave equation.Revista Brasileira de Ensino de Física, 30:1302.1–1302.5, 2008

Reference 25

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Observation 4e2cd2ee-e7f9-417d-99f6-cbdf2902689c · outbound

This paper cites Cambridge University Press, 7 edition, 1999.

Optical Physics-Based Generative Models Cambridge University Press, 7 edition, 1999

Reference 26

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raw_fallback, observed 2026-08-07T10:52:25.305746Z

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 22f03508-e61c-4717-a3a4-565e3d924948 · outbound

This paper cites On the partial difference equations of mathematical physics.

Optical Physics-Based Generative Models On the partial difference equations of mathematical physics

Reference 27

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raw_fallback, observed 2026-08-07T10:52:25.290527Z

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 0484060b-867b-48a2-9d96-890b8bcb50f4 · outbound

This paper cites Cambridge University Press, 1999.

Optical Physics-Based Generative Models Cambridge University Press, 1999

Reference 28

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verified fuzzy
raw_fallback, observed 2026-08-07T10:52:25.273081Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 27407997-3742-4c34-89f2-897f55b2387c · outbound

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

Optical Physics-Based Generative Models Score-Based Generative Modeling through Stochastic Differential Equations

Reference 29

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no resolver link, observed 2026-08-07T10:52:24.641496Z

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Observation 2cb42b8b-2865-4374-aced-64a59386874e · outbound

This paper cites Attention is all you need.Advances in Neural Information Processing Systems, 30:5998–6008, 2017.

Optical Physics-Based Generative Models Attention is all you need.Advances in Neural Information Processing Systems, 30:5998–6008, 2017

Reference 30

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raw_fallback, observed 2026-08-07T10:52:25.258033Z

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation bbddca6a-acc6-4b05-a3ad-75b6bb72b28f · outbound

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

Optical Physics-Based Generative Models U-net: Convolutional networks for biomedical image segmentation

Reference 31

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no resolver link, observed 2026-08-07T10:52:24.654864Z

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Observation 88fb2a0c-210d-493d-b185-f157fdb0d660 · outbound

This paper cites Practical bayesian optimization of machine learning algorithms.

Optical Physics-Based Generative Models Practical bayesian optimization of machine learning algorithms

Reference 32

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verified fuzzy
raw_fallback, observed 2026-08-07T10:52:25.224248Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 36820aef-9edd-40b0-a3fb-311c4b6539a1 · outbound

This paper cites Jax: composable transforma- tions of python+numpy programs.

Optical Physics-Based Generative Models Jax: composable transforma- tions of python+numpy programs

Reference 33

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raw_fallback, observed 2026-08-07T10:52:25.209503Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 635eea35-b1a9-4d89-a7e0-654de29ded65 · outbound

This paper cites Neural ordinary differential equations.

Optical Physics-Based Generative Models Neural ordinary differential equations

Reference 34

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no resolver link, observed 2026-08-07T10:52:24.669918Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T10:52:24.669918Z digest=sha256:ddfa2387a5e25371bb0319a0813a5d04590dd0edc81cda4ce2b81552dd4f4d53

Observation 4848176d-9caa-4ec1-8232-e0fb5d0d7914 · outbound

This paper cites FFJORD: Free-form Continuous Dynamics for Scalable Reversible Generative Models.

Optical Physics-Based Generative Models FFJORD: Free-form Continuous Dynamics for Scalable Reversible Generative Models

Reference 35

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 26488ff3-b7d3-4423-ab2a-d2905dd0fbe4 · outbound

This paper cites PFGM++: Unlocking the Potential of Physics-Inspired Generative Models.

Optical Physics-Based Generative Models PFGM++: Unlocking the Potential of Physics-Inspired Generative Models

Reference 36

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no resolver link, observed 2026-08-07T10:52:24.681026Z

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source=pdf_text observed=2026-08-07T10:52:24.681026Z digest=sha256:7dd820f2de901ca3ebd1705a1a6bf44aa1d8b4a0ce425631faebc4a6e3b1e2e7

Observation cf08bc46-ce01-4092-8a0d-4feeb620760b · outbound

This paper cites Gans trained by a two time-scale update rule converge to a local nash equilibrium.Advances in Neural Information Processing Systems, 30, 2017.

Optical Physics-Based Generative Models Gans trained by a two time-scale update rule converge to a local nash equilibrium.Advances in Neural Information Processing Systems, 30, 2017

Reference 37

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raw_fallback, observed 2026-08-07T10:52:25.184360Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T10:52:24.686047Z digest=sha256:bc995a4004853be755641332a71b37424656441368ddc0e080d97b3c47a3b2fb

Observation 2be964a2-c8a2-408a-9fa2-f0f9c30d421e · outbound

This paper cites A kernel two-sample test.The Journal of Machine Learning Research, 13:723–773, 2012.

Optical Physics-Based Generative Models A kernel two-sample test.The Journal of Machine Learning Research, 13:723–773, 2012

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:52:25.166424Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T10:52:24.690693Z digest=sha256:445d11e1d186516fd3003d85886b3ada05074ccea81ba6a5786f415d6b2d3193

Observation 50edf7b7-e3cd-47db-8893-c1606108d82d · outbound

This paper cites Elucidating the Design Space of Diffusion-Based Generative Models.

Optical Physics-Based Generative Models Elucidating the Design Space of Diffusion-Based Generative Models

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-07T10:52:24.694872Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T10:52:24.694872Z digest=sha256:eb82cdc7c5cf7690715893bb908db99d98c54973c14a71be13862217a021419b

Observation b2d794fa-14da-467c-92ec-0f70ec1f42ed · outbound

This paper cites Gradient-based learning applied to document recognition.Proceedings of the IEEE, 86(11):2278–2324, 1998.

Optical Physics-Based Generative Models Gradient-based learning applied to document recognition.Proceedings of the IEEE, 86(11):2278–2324, 1998

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-07T10:52:24.699586Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T10:52:24.699586Z digest=sha256:e5cb0bee2f775c90c2b1abd00021432df34119f6d38ecd22b59fdd3f70b0c091

Observation a95c9c72-075f-4517-a485-a7ecb01bc140 · outbound

This paper cites Visualizing data using t-sne.Journal of Machine Learning Research, 9:2579–2605, 2008.

Optical Physics-Based Generative Models Visualizing data using t-sne.Journal of Machine Learning Research, 9:2579–2605, 2008

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:52:25.139798Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T10:52:24.704196Z digest=sha256:3d76585dee7d49886e030fc292c12c34c330fb93d79341d9cc3aad1c4540af82

Observation 24db8641-db66-405b-87d9-a868ec0c2fef · outbound

This paper cites Diffusion Schr\"odinger Bridge with Applications to Score-Based Generative Modeling.

Optical Physics-Based Generative Models Diffusion Schr\"odinger Bridge with Applications to Score-Based Generative Modeling

Reference 42

Resolution
unresolved
no resolver link, observed 2026-08-07T10:52:24.708826Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T10:52:24.708826Z digest=sha256:5d5b48a6c1049b4fc93e833b28459a9c67314de14902de8e91c479116bb2a748

Observation 77185826-5e8c-4a13-b8a2-f52c61e20eed · outbound

This paper cites Learning approach to optical tomography.Optica, 2(6):517–522, 2015.

Optical Physics-Based Generative Models Learning approach to optical tomography.Optica, 2(6):517–522, 2015

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:52:25.124186Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T10:52:24.713919Z digest=sha256:11f704b4efaece9081aec9ac31737cb7c7cfaac8df406aa685f58b107c181795

Observation 2b8fc164-c768-4265-8dc0-09fb5664974a · outbound

This paper cites Photonics for artificial intelligence and neuromorphic computing.Nature Photonics, 15(2):102–114, 2021.

Optical Physics-Based Generative Models Photonics for artificial intelligence and neuromorphic computing.Nature Photonics, 15(2):102–114, 2021

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:52:25.109365Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T10:52:24.718641Z digest=sha256:3fba9584813af08eb0540ec8e088992700aa0295df17f81f8fc723e668a852d0

Observation 7192dcee-622b-4ac5-8cd6-e80fa6281f74 · outbound

This paper cites Inference in artificial intelligence with deep optics and photonics.Nature, 588(7836):39–47, 2020.

Optical Physics-Based Generative Models Inference in artificial intelligence with deep optics and photonics.Nature, 588(7836):39–47, 2020

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:52:25.096143Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T10:52:24.723665Z digest=sha256:6643a6fcff947bd124b5cffe1a1163b932e9ce6f09a96ec4303f5501ccc8bc9e

Observation fb576110-bd44-47bb-a1dd-c82d5609f818 · outbound

This paper cites All-optical machine learning using diffractive deep neural networks.Science, 361(6406):1004–1008, 2018.

Optical Physics-Based Generative Models All-optical machine learning using diffractive deep neural networks.Science, 361(6406):1004–1008, 2018

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:52:25.080728Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T10:52:24.728483Z digest=sha256:e781be5e2c04588f5b51ef3022b4f1cd3c61526cb428caf91477317d17b1fff0

Observation 6b1931cd-347a-4a5a-a741-843dbd114360 · outbound

This paper cites Spatiotemporal light control with active metasurfaces.Science, 364(6441), 2019.

Optical Physics-Based Generative Models Spatiotemporal light control with active metasurfaces.Science, 364(6441), 2019

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:52:25.062820Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T10:52:24.733050Z digest=sha256:15d9f5859e15ceaac0aa60cb0a49a6a299af19f28eb6981f58dd989d1f8746ca

Observation 8ac5625c-db03-4c0c-920c-ace53cc0d7d8 · outbound

This paper cites 0", "6", and.

Optical Physics-Based Generative Models 0", "6", and

Reference 48

Resolution
malformed identifier
raw_fallback, observed 2026-08-07T10:52:25.045641Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T10:52:24.737912Z digest=sha256:d1174ff9624d5404ac581060ae067e7532c5f8effe9662dbc8be98cae94dc7cf

Pith citing papers

Observation 6c873bdc-b9d5-4132-a9c4-9aea04aca642 · inbound

Strategic Alignment Patterns in National AI Policies cites this paper.

Strategic Alignment Patterns in National AI Policies Optical Physics-Based Generative Models

Reference 8

Resolution
verified exact
local_arxiv, observed 2026-08-06T19:32:18.820794Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T19:32:18.608360Z digest=sha256:682c532fe7136fb5dac4a29cd40ba43ee8812589f38dd7ad8d6b9c3f0d480dbc