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Paper Citation Record · LEDGER

Fractal Flow: Hierarchical and Interpretable Normalizing Flow via Topic Modeling and Recursive Strategy

As of 7 August 2026, this Paper Citation Record lists 33 of 33 outbound references and 1 inbound Pith citation observation for arXiv:2508.19750.

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

pith.paper-citation-record.v1
2508.19750 v1

Coverage vector

measured 33 of 33 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-05T15:35:26.961392Z

measured 34 of 34 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-27T15:22:40.822607Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

33 of 33 outbound references displayed

  • verified exact1
  • verified fuzzy19
  • unresolved13
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

0
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

Observation b1d3e2b3-1ce8-4d6b-b779-9c9341bdb420 · outbound

This paper cites Fractal structures in nonlinear dynamics.

Fractal Flow: Hierarchical and Interpretable Normalizing Flow via Topic Modeling and Recursive Strategy Fractal structures in nonlinear dynamics

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T15:35:27.562463Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-05T15:35:26.775352Z digest=sha256:ee8d9f55415ade60e5329ca88c6a0bf69f2d646c0a14eee8e49401bc279c832b

Observation 1f7e1ce3-594f-429f-af46-1b1c5be8ea46 · outbound

This paper cites Neural flow diffusion models: Learnable forward process for improved diffusion modelling.

Fractal Flow: Hierarchical and Interpretable Normalizing Flow via Topic Modeling and Recursive Strategy Neural flow diffusion models: Learnable forward process for improved diffusion modelling

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T15:35:27.538963Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-05T15:35:26.780813Z digest=sha256:7e76e187e9f956e17d8a394dca9fdc478697ae3105f581ee36882f15ad44e01a

Observation 2fe7daf2-e34f-437c-a227-66418f1f5915 · outbound

This paper cites Latent dirichlet allocation.

Fractal Flow: Hierarchical and Interpretable Normalizing Flow via Topic Modeling and Recursive Strategy Latent dirichlet allocation

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T15:35:27.520198Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-05T15:35:26.785982Z digest=sha256:9cfac53ffe15a7070bf8177aa4168be9acbba904116bf6e906a3725f3567faea

Observation 0664853d-6861-4353-904e-b293d1d6bdd3 · outbound

This paper cites Topic modeling using latent dirichlet allocation: A survey.

Fractal Flow: Hierarchical and Interpretable Normalizing Flow via Topic Modeling and Recursive Strategy Topic modeling using latent dirichlet allocation: A survey

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T15:35:27.497292Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-05T15:35:26.792007Z digest=sha256:47b55036005fcde01da8afbe2dc0973268fb90b5521e0388ad23b448561f9bff

Observation 7f05134e-4487-46d4-b01a-ca9be349ecc1 · outbound

This paper cites Density estimation using Real NVP.

Fractal Flow: Hierarchical and Interpretable Normalizing Flow via Topic Modeling and Recursive Strategy Density estimation using Real NVP

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T15:35:27.473444Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-05T15:35:26.798052Z digest=sha256:aa3e0a43cdf0a7b80d600715a6f1be2e76bb21cbd9739e247e65aabaa7fd23f3

Observation 3980040f-cc2a-4b92-a75b-1d1c6c61b54a · outbound

This paper cites Normalizing Flow with Variational Latent Representation.

Fractal Flow: Hierarchical and Interpretable Normalizing Flow via Topic Modeling and Recursive Strategy Normalizing Flow with Variational Latent Representation

Reference 6

Resolution
verified exact
local_arxiv, observed 2026-08-05T15:35:27.155421Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-05T15:35:26.802950Z digest=sha256:eda5541bd22bacbe2ab84cd2ae4eae832383f16e8a9bbb29b3a0612d4d11f5e2

Observation 3ec2aaf8-0230-4c85-a374-6306c8ae4afc · outbound

This paper cites Neural spline flows.

Fractal Flow: Hierarchical and Interpretable Normalizing Flow via Topic Modeling and Recursive Strategy Neural spline flows

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T15:35:27.453113Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-05T15:35:26.812527Z digest=sha256:5bcf72d6266cdd357f4fd949401b0d799cf64c8adff0d113a9c6460b0856ce9b

Observation 437094ea-e29a-481a-9830-67d57028aeb0 · outbound

This paper cites Mean Flows for One-step Generative Modeling.

Fractal Flow: Hierarchical and Interpretable Normalizing Flow via Topic Modeling and Recursive Strategy Mean Flows for One-step Generative Modeling

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-05T15:35:26.820491Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T15:35:26.820491Z digest=sha256:68368a14275b5c2ff524aa1d7a92058dde2aecc8a43586be616bf4edf9e5cba9

Observation 0e9ebf40-069d-4a9d-8030-3f05b72d2369 · outbound

This paper cites STARFlow: Scaling Latent Normalizing Flows for High-resolution Image Synthesis.

Fractal Flow: Hierarchical and Interpretable Normalizing Flow via Topic Modeling and Recursive Strategy STARFlow: Scaling Latent Normalizing Flows for High-resolution Image Synthesis

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-05T15:35:26.827573Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T15:35:26.827573Z digest=sha256:f85635b36fa56dddb3aba5f01e5bf28a8fcda1e157d0a720cb68902dbed50b3b

Observation 25c2c383-6333-4d54-9513-78c969129218 · outbound

This paper cites beta-vae: Learning basic visual concepts with a constrained variational framework.

Fractal Flow: Hierarchical and Interpretable Normalizing Flow via Topic Modeling and Recursive Strategy beta-vae: Learning basic visual concepts with a constrained variational framework

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-05T15:35:26.838393Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T15:35:26.838393Z digest=sha256:72582d5b4dc529e7e1ab94fb8eb6aaa08c43c7e4e472212471743b347430104d

Observation 18ed1bab-98f7-47b3-bf68-368ae7c26621 · outbound

This paper cites Denoising diffusion probabilistic models.

Fractal Flow: Hierarchical and Interpretable Normalizing Flow via Topic Modeling and Recursive Strategy Denoising diffusion probabilistic models

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-05T15:35:26.848769Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T15:35:26.848769Z digest=sha256:760ae6bf8f0941f83e07f55211381b6564198ed05266e46234cb7649e487852b

Observation 3dca1747-ee1e-43c3-b65d-70c8fad7b1db · outbound

This paper cites Semi-supervised learning with normalizing flows.

Fractal Flow: Hierarchical and Interpretable Normalizing Flow via Topic Modeling and Recursive Strategy Semi-supervised learning with normalizing flows

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T15:35:27.407474Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-05T15:35:26.855767Z digest=sha256:91c5bc6b59da93620ec138d4e8a0014254daa17ced00f96bec6c1c323a65730e

Observation 80e34d95-c15d-44ec-bb8d-17098263e729 · outbound

This paper cites Auto-Encoding Variational Bayes.

Fractal Flow: Hierarchical and Interpretable Normalizing Flow via Topic Modeling and Recursive Strategy Auto-Encoding Variational Bayes

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-05T15:35:26.860428Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T15:35:26.860428Z digest=sha256:2c09b60c510bf671a0f2300e1c4a92c44870f4fff064ef9d58ceb142cac55b2e

Observation b44cf878-03bb-4877-be5b-6b098f9bf264 · outbound

This paper cites Glow: Generative flow with invertible 1x1 convolutions.

Fractal Flow: Hierarchical and Interpretable Normalizing Flow via Topic Modeling and Recursive Strategy Glow: Generative flow with invertible 1x1 convolutions

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T15:35:27.391307Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-05T15:35:26.865454Z digest=sha256:dd6bf297e0f50c536660426f1afa3746ed2cc670c77da0c4a4e5b6cc49c48d08

Observation 7bcb1512-f9a5-4eb3-9503-aa79c3e5011c · outbound

This paper cites Improved variational inference with inverse autoregressive flow.

Fractal Flow: Hierarchical and Interpretable Normalizing Flow via Topic Modeling and Recursive Strategy Improved variational inference with inverse autoregressive flow

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T15:35:27.374319Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-05T15:35:26.870141Z digest=sha256:8623ed41f037a50c6bcccc4449115860dec9d9dd01ed1c8814bd1df23bed9ff7

Observation 9d8456f2-f2f9-4240-9b8a-2866e39d3033 · outbound

This paper cites Jet: A Modern Transformer-Based Normalizing Flow.

Fractal Flow: Hierarchical and Interpretable Normalizing Flow via Topic Modeling and Recursive Strategy Jet: A Modern Transformer-Based Normalizing Flow

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-05T15:35:26.874626Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T15:35:26.874626Z digest=sha256:f697a6bcc796795c101ebe8b03ea7c8164cb28f75bb7b2bed2e066dc4a2a1ddd

Observation 09d174ba-26c4-4761-9d0a-c2a5a2720e30 · outbound

This paper cites On the representation of continuous functions of several variables by superpositions of continuous functions of a smaller number of variables.

Fractal Flow: Hierarchical and Interpretable Normalizing Flow via Topic Modeling and Recursive Strategy On the representation of continuous functions of several variables by superpositions of continuous functions of a smaller number of variables

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-05T15:35:26.880236Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T15:35:26.880236Z digest=sha256:92e14d6de3cb14ac3bf749d202f267d9bb178755a52632d8c4e4d2d0f78cb6bd

Observation 9033fc7b-e31b-4f89-bebe-d93523ce2f5a · outbound

This paper cites Variational Inference of Disentangled Latent Concepts from Unlabeled Observations.

Fractal Flow: Hierarchical and Interpretable Normalizing Flow via Topic Modeling and Recursive Strategy Variational Inference of Disentangled Latent Concepts from Unlabeled Observations

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-05T15:35:26.885449Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T15:35:26.885449Z digest=sha256:ee9500555bb73800e975b66fac1fec192964fea2b429b29114118ba9ac37de5e

Observation dcbc3184-dfb1-4761-874e-2e36b48b6a2d · outbound

This paper cites Fractalnet: Ultra-deep neural networks without residuals.

Fractal Flow: Hierarchical and Interpretable Normalizing Flow via Topic Modeling and Recursive Strategy Fractalnet: Ultra-deep neural networks without residuals

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T15:35:27.346155Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-05T15:35:26.891359Z digest=sha256:b754221c0c7f8fcb409580d7fcd55e59be17186f15cc9935966caf5a883db178

Observation 2ddb99bb-d10a-4e62-add3-81f5331f3015 · outbound

This paper cites Mage: Masked generative encoder to unify representation learning and image synthesis.

Fractal Flow: Hierarchical and Interpretable Normalizing Flow via Topic Modeling and Recursive Strategy Mage: Masked generative encoder to unify representation learning and image synthesis

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T15:35:27.329385Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-05T15:35:26.896446Z digest=sha256:a63bbe85133bd7e5b5f46082a74394bf90d2eae4018b28862b870825d03a98aa

Observation 2968b32b-715f-4bad-a7d8-e6f324955fcc · outbound

This paper cites Fractal Generative Models.

Fractal Flow: Hierarchical and Interpretable Normalizing Flow via Topic Modeling and Recursive Strategy Fractal Generative Models

Reference 21

Resolution
unresolved
no resolver link, observed 2026-08-05T15:35:26.901402Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T15:35:26.901402Z digest=sha256:ed17cbedda9d4bcff488b60e1e240d8838b9ab30178fb6e4fb284f4c8ae394a1

Observation 713a9cb2-c74a-471d-8455-385604795a92 · outbound

This paper cites KAN: Kolmogorov-Arnold Networks.

Fractal Flow: Hierarchical and Interpretable Normalizing Flow via Topic Modeling and Recursive Strategy KAN: Kolmogorov-Arnold Networks

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-05T15:35:26.906142Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T15:35:26.906142Z digest=sha256:e573eb60147af826a853142b28ccaadf85577b5470ee3d9729e76fbfcdeba0e0

Observation a7e56a9a-600f-45e4-8eba-02d6ef51f7e4 · outbound

This paper cites Masked autoregressive flow for density estimation.

Fractal Flow: Hierarchical and Interpretable Normalizing Flow via Topic Modeling and Recursive Strategy Masked autoregressive flow for density estimation

Reference 23

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T15:35:27.313396Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-05T15:35:26.911259Z digest=sha256:3a2ef667c52fb578e45a5b4ef51b0d3d349eaa809eb9f837974cc5742b35106b

Observation 09ed6622-c574-4672-95c9-4403f38497b6 · outbound

This paper cites Normalizing flows for probabilistic modeling and inference.

Fractal Flow: Hierarchical and Interpretable Normalizing Flow via Topic Modeling and Recursive Strategy Normalizing flows for probabilistic modeling and inference

Reference 24

Resolution
unresolved
no resolver link, observed 2026-08-05T15:35:26.916655Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T15:35:26.916655Z digest=sha256:1cb14864c6878ffee88f308c669487355e289785ec44037e6e2e54aa7de17b8f

Observation 26c0a1ce-586a-4dc3-82e8-ebb5bce64cbb · outbound

This paper cites Image transformer.

Fractal Flow: Hierarchical and Interpretable Normalizing Flow via Topic Modeling and Recursive Strategy Image transformer

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T15:35:27.287692Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-05T15:35:26.921588Z digest=sha256:a013f2312c70ab7d50b0b22b10bb1cbce7ad10ff6a3eeab9e9fd96c358f962ff

Observation 8ef94f30-1cde-4d76-ad22-afd70804b2e2 · outbound

This paper cites High-resolution image synthesis with latent diffusion models.

Fractal Flow: Hierarchical and Interpretable Normalizing Flow via Topic Modeling and Recursive Strategy High-resolution image synthesis with latent diffusion models

Reference 26

Resolution
unresolved
no resolver link, observed 2026-08-05T15:35:26.927172Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T15:35:26.927172Z digest=sha256:92b7c061073dcc8c1eb57149940058ef5433dab41e1ff3173f6861b1a5eb7e4d

Observation 3d8162ff-f9f8-48e8-8c09-22a3f721adf0 · outbound

This paper cites Visual autoregressive modeling: Scalable image generation via next-scale prediction.

Fractal Flow: Hierarchical and Interpretable Normalizing Flow via Topic Modeling and Recursive Strategy Visual autoregressive modeling: Scalable image generation via next-scale prediction

Reference 27

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T15:35:27.260192Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-05T15:35:26.932636Z digest=sha256:be51147b2dcc4e042d84f3fac467cd7233c3a5603a3a4226154642e6438f094b

Observation d5c03004-adcc-49d9-8b9b-7aa638cc9b52 · outbound

This paper cites Conditional image generation with pixelcnn decoders.

Fractal Flow: Hierarchical and Interpretable Normalizing Flow via Topic Modeling and Recursive Strategy Conditional image generation with pixelcnn decoders

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T15:35:27.242100Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-05T15:35:26.937655Z digest=sha256:6bbcf3ab9b68a3e2da2470c4671786866ecc4d8155a09417baefa37b42b53a3c

Observation f68f5cfc-8c40-4edd-af3f-4cbc334f1f7e · outbound

This paper cites Pixel recurrent neural networks.

Fractal Flow: Hierarchical and Interpretable Normalizing Flow via Topic Modeling and Recursive Strategy Pixel recurrent neural networks

Reference 29

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T15:35:27.225186Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-05T15:35:26.942408Z digest=sha256:8554c33df36988d41b516ccb0f2d4e67a8e08a5955f36f700290bd330d274061

Observation 63452888-6713-427c-8f5f-f9a07b7b5f3f · outbound

This paper cites Generative Latent Flow.

Fractal Flow: Hierarchical and Interpretable Normalizing Flow via Topic Modeling and Recursive Strategy Generative Latent Flow

Reference 30

Resolution
unresolved
no resolver link, observed 2026-08-05T15:35:26.946847Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T15:35:26.946847Z digest=sha256:a17b4a21af0169f64ae881d68bd145b04a97b29c0687c1c9f7b754d5a03d3230

Observation 71215524-7d46-4857-a467-f977ce92549d · outbound

This paper cites Hierarchical gaussian mixture normalizing flow modeling for unified anomaly detection.

Fractal Flow: Hierarchical and Interpretable Normalizing Flow via Topic Modeling and Recursive Strategy Hierarchical gaussian mixture normalizing flow modeling for unified anomaly detection

Reference 31

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T15:35:27.209728Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-05T15:35:26.952284Z digest=sha256:c574902e73f5581782fdd7252cc51eca0f9b35b60fe81c5e98e53f5aeddc1d07

Observation 12ff90f0-a667-4807-a99a-09c82c7ab352 · outbound

This paper cites Deep learning for geophysics: Current and future trends.

Fractal Flow: Hierarchical and Interpretable Normalizing Flow via Topic Modeling and Recursive Strategy Deep learning for geophysics: Current and future trends

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T15:35:27.189571Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-05T15:35:26.956850Z digest=sha256:5d399f0030d13589dc7ff78cc9eadb433928bc30116e1cda9c5dcacad54dd576

Observation dc82d387-339a-416b-b70c-ca36e702c11f · outbound

This paper cites Transformers without normalization.

Fractal Flow: Hierarchical and Interpretable Normalizing Flow via Topic Modeling and Recursive Strategy Transformers without normalization

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T15:35:27.173086Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-05T15:35:26.961392Z digest=sha256:45c3144efde1a7b1ff9feaa2c3f6ae1f72b659b145207151abec93a64a7f4fc4

Pith citing papers

Observation 8e5979b0-e19b-4d08-b88c-91d5c3f2ef1c · inbound

Learning the Universe: Posterior Reliability of Neural Generative Models in High-Dimensional Field-Level Inference of Cosmic Initial Conditions cites this paper.

Learning the Universe: Posterior Reliability of Neural Generative Models in High-Dimensional Field-Level Inference of Cosmic Initial Conditions Fractal Flow: Hierarchical and Interpretable Normalizing Flow via Topic Modeling and Recursive Strategy

Reference 131

Resolution
verified exact
arxiv_id, observed 2026-06-27T19:11:10.689242Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-06-27T15:22:40.822607Z digest=sha256:0f27e6658ba62795f3fe85e3f310e0cf6f65c42d2375c6a8c33cac85139be8df