Paper Citation Record · LEDGER

JAPAN: Joint Adaptive Prediction Areas with Normalising-Flows

As of 8 August 2026, this Paper Citation Record lists 50 of 50 outbound references and 2 inbound Pith citation observations for arXiv:2505.23196.

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

pith.paper-citation-record.v1
2505.23196 v1

Coverage vector

measured 50 of 50 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T12:59:44.124291Z

measured 52 of 52 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 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-29T20:45:52.977412Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-29T21:03:58.860334Z

Reference resolution

50 of 50 outbound references displayed

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External citation measurements

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Outbound references

Observation 0f608699-7b0c-4943-9107-bd980729966d · outbound

This paper cites Alaa and Mihaela van der Schaar.

JAPAN: Joint Adaptive Prediction Areas with Normalising-Flows Alaa and Mihaela van der Schaar

Reference 1

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Observation cf2d39e4-94be-4278-be50-cf86a7939b43 · outbound

This paper cites Building Normalizing Flows with Stochastic Interpolants.

JAPAN: Joint Adaptive Prediction Areas with Normalising-Flows Building Normalizing Flows with Stochastic Interpolants

Reference 2

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Observation 03942050-c889-4fe8-b937-88c421190e94 · outbound

This paper cites Angelopoulos and Stephen Bates.

JAPAN: Joint Adaptive Prediction Areas with Normalising-Flows Angelopoulos and Stephen Bates

Reference 3

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Observation 9953ee32-c068-4bfb-94a2-534e0cc616bd · outbound

This paper cites Candes, Aaditya Ramdas, and Ryan J.

JAPAN: Joint Adaptive Prediction Areas with Normalising-Flows Candes, Aaditya Ramdas, and Ryan J

Reference 4

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Observation c643e030-4016-490f-839e-0a16a466ca4b · outbound

This paper cites Candes, Aaditya Ramdas, and Ryan J.

JAPAN: Joint Adaptive Prediction Areas with Normalising-Flows Candes, Aaditya Ramdas, and Ryan J

Reference 5

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Observation addefb7d-96c5-4dc1-af88-9b5bfa606ebb · outbound

This paper cites Duvenaud.

JAPAN: Joint Adaptive Prediction Areas with Normalising-Flows Duvenaud

Reference 6

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Source-reported events for the cited work

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Observation 38d699f7-acaa-4ed4-87c1-85a1d0259d41 · outbound

This paper cites Exact and robust conformal inference methods for predictive machine learning with dependent data.

JAPAN: Joint Adaptive Prediction Areas with Normalising-Flows Exact and robust conformal inference methods for predictive machine learning with dependent data

Reference 7

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Observation fa856c65-b22b-47aa-b6e3-abbaf0a69695 · outbound

This paper cites Pappas, and Lars Lindemann.

JAPAN: Joint Adaptive Prediction Areas with Normalising-Flows Pappas, and Lars Lindemann

Reference 8

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Observation ee465c07-a8f6-42c1-a19c-daec48130421 · outbound

This paper cites Normalizing Flows for Conformal Regression.

JAPAN: Joint Adaptive Prediction Areas with Normalising-Flows Normalizing Flows for Conformal Regression

Reference 9

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Observation 1b8d129d-a398-472c-97c0-69f87609406d · outbound

This paper cites Density estimation using real nvp, 2017.

JAPAN: Joint Adaptive Prediction Areas with Normalising-Flows Density estimation using real nvp, 2017

Reference 10

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Observation 1d38d7a8-302f-4b77-bfd0-672961988496 · outbound

This paper cites Multiple Comparisons among Means.

JAPAN: Joint Adaptive Prediction Areas with Normalising-Flows Multiple Comparisons among Means

Reference 11

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Source-reported events for the cited work

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Observation 120eabc2-2db4-429a-8f63-35cb7c975e3c · outbound

This paper cites Neural spline flows, 2019.

JAPAN: Joint Adaptive Prediction Areas with Normalising-Flows Neural spline flows, 2019

Reference 12

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Observation ceb74cc3-e430-460b-a75a-869715a3667e · outbound

This paper cites Kernelised normalising flows, 2023.

JAPAN: Joint Adaptive Prediction Areas with Normalising-Flows Kernelised normalising flows, 2023

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:59:51.276749Z

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Observation 584bec32-003b-4ecc-8ab3-e9304172c05f · outbound

This paper cites JANET: Joint Adaptive predictioN-region Estimation for Time-series.

JAPAN: Joint Adaptive Prediction Areas with Normalising-Flows JANET: Joint Adaptive predictioN-region Estimation for Time-series

Reference 14

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Observation 2e4804ec-ac87-4dca-a472-b0cdfda83ec1 · outbound

This paper cites CONTRA : Conformal Prediction Region via Normalizing Flow Transformation.

JAPAN: Joint Adaptive Prediction Areas with Normalising-Flows CONTRA : Conformal Prediction Region via Normalizing Flow Transformation

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:59:51.093116Z

Source-reported events for the cited work

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Observation 1d2e83a1-105c-4721-a41d-5f047feef735 · outbound

This paper cites Calibrated Multiple - Output Quantile Regression with Representation Learning.

JAPAN: Joint Adaptive Prediction Areas with Normalising-Flows Calibrated Multiple - Output Quantile Regression with Representation Learning

Reference 16

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Source-reported events for the cited work

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Observation 125f7340-b5f7-4fd5-97c0-f4e8d9f80b5c · outbound

This paper cites Multi-scale attention flow for probabilistic time series forecasting, 2023.

JAPAN: Joint Adaptive Prediction Areas with Normalising-Flows Multi-scale attention flow for probabilistic time series forecasting, 2023

Reference 17

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Source-reported events for the cited work

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Observation 2300a00d-52e2-4d1d-a639-937d1bcc1d2f · outbound

This paper cites Gammerman, V.

JAPAN: Joint Adaptive Prediction Areas with Normalising-Flows Gammerman, V

Reference 18

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Observation ae17acff-0f78-48ef-8d9d-295f293b957e · outbound

This paper cites Adaptive conformal inference under distribution shift, 2021.

JAPAN: Joint Adaptive Prediction Areas with Normalising-Flows Adaptive conformal inference under distribution shift, 2021

Reference 19

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Observation 954fd663-9ed0-411c-b23d-77dffbfe5e42 · outbound

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JAPAN: Joint Adaptive Prediction Areas with Normalising-Flows Unresolved cited work

Reference 20

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Observation e28a32b0-b8da-48fb-9350-0d86fe463698 · outbound

This paper cites Flexible distribution-free conditional predictive bands using density estimators.

JAPAN: Joint Adaptive Prediction Areas with Normalising-Flows Flexible distribution-free conditional predictive bands using density estimators

Reference 21

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Observation 47e27390-2831-4c24-9b24-d13279392e3e · outbound

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JAPAN: Joint Adaptive Prediction Areas with Normalising-Flows Unresolved cited work

Reference 22

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Observation 0998ef0c-7bbf-4624-9390-89be2bcefbb2 · outbound

This paper cites Conformal uncertainty sets for robust optimization.

JAPAN: Joint Adaptive Prediction Areas with Normalising-Flows Conformal uncertainty sets for robust optimization

Reference 23

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Observation 88442ecb-31c0-4ede-9193-209b3999ad49 · outbound

This paper cites Kingma and Prafulla Dhariwal.

JAPAN: Joint Adaptive Prediction Areas with Normalising-Flows Kingma and Prafulla Dhariwal

Reference 24

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Observation fa31f506-a1b1-4143-8ee8-ee863258a968 · outbound

This paper cites Neural relational inference for interacting systems, 2018.

JAPAN: Joint Adaptive Prediction Areas with Normalising-Flows Neural relational inference for interacting systems, 2018

Reference 25

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Observation fafce59a-d4d7-4e07-977f-29f685aa69f7 · outbound

This paper cites Distribution Free Prediction Sets.

JAPAN: Joint Adaptive Prediction Areas with Normalising-Flows Distribution Free Prediction Sets

Reference 26

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JAPAN: Joint Adaptive Prediction Areas with Normalising-Flows Unresolved cited work

Reference 27

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Observation 0ab5f9ee-9070-4ef4-8960-8e9f3b242154 · outbound

This paper cites Conformal multi-target regression using neural networks.

JAPAN: Joint Adaptive Prediction Areas with Normalising-Flows Conformal multi-target regression using neural networks

Reference 28

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Observation c0b96c80-8f6b-4d98-bfb7-f140d300e47e · outbound

This paper cites Copula-based conformal prediction for multi-target regression, 2021.

JAPAN: Joint Adaptive Prediction Areas with Normalising-Flows Copula-based conformal prediction for multi-target regression, 2021

Reference 29

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Observation cdf90f14-b573-4bb6-9320-5a4d1d451d2a · outbound

This paper cites Inductive confidence machines for regression.

JAPAN: Joint Adaptive Prediction Areas with Normalising-Flows Inductive confidence machines for regression

Reference 30

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Source-reported events for the cited work

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Observation e0488145-208d-4d09-b46a-8d8b65fb1ffd · outbound

This paper cites Masked autoregressive flow for density estimation, 2018.

JAPAN: Joint Adaptive Prediction Areas with Normalising-Flows Masked autoregressive flow for density estimation, 2018

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:59:48.358596Z

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Observation 1b3359b6-b235-4843-ac1f-ea0f7ee9c95b · outbound

This paper cites Normalizing flows for probabilistic modeling and inference, 2021.

JAPAN: Joint Adaptive Prediction Areas with Normalising-Flows Normalizing flows for probabilistic modeling and inference, 2021

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:59:48.065683Z

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Observation 62c56044-da20-4793-9aae-059c278d4857 · outbound

This paper cites Probabilistic Conformal Prediction with Approximate Conditional Validity.

JAPAN: Joint Adaptive Prediction Areas with Normalising-Flows Probabilistic Conformal Prediction with Approximate Conditional Validity

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:59:47.832088Z

Source-reported events for the cited work

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Observation 590e080d-22ca-4560-a678-290d80281d1e · outbound

This paper cites Multivariate probabilistic time series forecasting via conditioned normalizing flows, 2021.

JAPAN: Joint Adaptive Prediction Areas with Normalising-Flows Multivariate probabilistic time series forecasting via conditioned normalizing flows, 2021

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:59:47.582333Z

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Observation ce346c2b-160a-4dd4-8619-f3b05af1bde7 · outbound

This paper cites Conformalized Quantile Regression.

JAPAN: Joint Adaptive Prediction Areas with Normalising-Flows Conformalized Quantile Regression

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:59:47.305215Z

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Observation bdb124fa-d5b4-45a8-8214-e14e22dec064 · outbound

This paper cites Pythonrobotics: a python code collection of robotics algorithms, 2018.

JAPAN: Joint Adaptive Prediction Areas with Normalising-Flows Pythonrobotics: a python code collection of robotics algorithms, 2018

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:59:47.030843Z

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Observation 0829f36c-cd4a-4c7f-b7eb-f505a01feae3 · outbound

This paper cites A tutorial on conformal prediction.

JAPAN: Joint Adaptive Prediction Areas with Normalising-Flows A tutorial on conformal prediction

Reference 37

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Source-reported events for the cited work

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Observation 5b79abdb-6eba-4d34-b1f1-de1f801b9a13 · outbound

This paper cites Kingma, Abhishek Kumar, Stefano Ermon, and Ben Poole.

JAPAN: Joint Adaptive Prediction Areas with Normalising-Flows Kingma, Abhishek Kumar, Stefano Ermon, and Ben Poole

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:59:46.793572Z

Source-reported events for the cited work

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Observation 48397b43-e2c5-438c-8e5b-16bed3cc75aa · outbound

This paper cites Maximum likelihood training of score-based diffusion models.

JAPAN: Joint Adaptive Prediction Areas with Normalising-Flows Maximum likelihood training of score-based diffusion models

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:59:46.585937Z

Source-reported events for the cited work

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Observation 482cc07a-ee4c-4d38-86a3-e285c3607006 · outbound

This paper cites Multi-Target Regression via Input Space Expansion: Treating Targets as Inputs.

JAPAN: Joint Adaptive Prediction Areas with Normalising-Flows Multi-Target Regression via Input Space Expansion: Treating Targets as Inputs

Reference 40

Resolution: verified exact; local_arxiv, observed 2026-08-07T12:59:44.443966Z

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Observation 7181225c-84fa-43fc-bb81-a0c3495d5bc8 · outbound

This paper cites Alaa, and Mihaela van der Schaar.

JAPAN: Joint Adaptive Prediction Areas with Normalising-Flows Alaa, and Mihaela van der Schaar

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:59:46.383577Z

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.

Observation f0df7f6b-b9c0-434e-8fa5-bfdf7b845936 · outbound

This paper cites Copula conformal prediction for multi-step time series prediction.

JAPAN: Joint Adaptive Prediction Areas with Normalising-Flows Copula conformal prediction for multi-step time series prediction

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:59:46.118592Z

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.

Observation 243a0eac-a01e-4904-8356-6cd2db06d48c · outbound

This paper cites Accurate quantitative estimation of energy performance of residential buildings using statistical machine learning tools.

JAPAN: Joint Adaptive Prediction Areas with Normalising-Flows Accurate quantitative estimation of energy performance of residential buildings using statistical machine learning tools

Reference 43

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Source-reported events for the cited work

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Observation 7cd40847-cb66-4ce1-b27a-9db9c0fc3655 · outbound

This paper cites Reciprocal Velocity Obstacles for real-time multi-agent navigation.

JAPAN: Joint Adaptive Prediction Areas with Normalising-Flows Reciprocal Velocity Obstacles for real-time multi-agent navigation

Reference 44

Resolution: metadata mismatch; raw_fallback, observed 2026-08-07T12:59:44.302619Z

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.

Observation c15f6a52-5bad-45d5-ad59-c800f8a1d670 · outbound

This paper cites Attention is All you Need.

JAPAN: Joint Adaptive Prediction Areas with Normalising-Flows Attention is All you Need

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:59:45.921013Z

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.

Observation 50cfcec1-d7fd-4bbc-a694-f6c013188e8b · outbound

This paper cites Algorithmic learning in a random world, volume 29.

JAPAN: Joint Adaptive Prediction Areas with Normalising-Flows Algorithmic learning in a random world, volume 29

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-07T12:59:43.953421Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9a332400-d777-45d1-83a5-282ea64d2e44 · outbound

This paper cites Probabilistic Conformal Prediction Using Conditional Random Samples.

JAPAN: Joint Adaptive Prediction Areas with Normalising-Flows Probabilistic Conformal Prediction Using Conditional Random Samples

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:59:45.621924Z

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.

Observation 611cb678-9d30-4dd4-be58-285776eb286a · outbound

This paper cites Learning Likelihoods with Conditional Normalizing Flows.

JAPAN: Joint Adaptive Prediction Areas with Normalising-Flows Learning Likelihoods with Conditional Normalizing Flows

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:59:45.404925Z

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.

Observation cacd8b10-d594-43eb-8e97-1273a6549281 · outbound

This paper cites Normalizing Flows are Capable Generative Models , December 2024.

JAPAN: Joint Adaptive Prediction Areas with Normalising-Flows Normalizing Flows are Capable Generative Models , December 2024

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:59:45.171262Z

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.

Observation 20dd01eb-743b-4ff9-abd0-5e5608c0ea5f · outbound

This paper cites Conformalized adaptive forecasting of heterogeneous trajectories, 2024.

JAPAN: Joint Adaptive Prediction Areas with Normalising-Flows Conformalized adaptive forecasting of heterogeneous trajectories, 2024

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:59:44.914979Z

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.

Pith citing papers

Observation 14eab6db-71e1-4c46-ae46-f25cb44b2b85 · inbound

Multivariate Standardized Residuals for Conformal Prediction cites this paper.

Multivariate Standardized Residuals for Conformal Prediction JAPAN: Joint Adaptive Prediction Areas with Normalising-Flows

Reference 7

Resolution: verified exact; arxiv_id, observed 2026-05-19T03:32:01.701301Z

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.

Observation f3605fbb-e3a7-4434-b3a8-88a3d00c2845 · inbound

A Post-Processing Conformal Prediction Approach for Conditional Coverage via Pivotal Scores cites this paper.

A Post-Processing Conformal Prediction Approach for Conditional Coverage via Pivotal Scores JAPAN: Joint Adaptive Prediction Areas with Normalising-Flows

Reference 5

Resolution: verified exact; arxiv_id, observed 2026-06-29T21:03:58.862002Z

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.