Paper Citation Record · LEDGER

Order-Agnostic Autoregressive Modelling with Missing Data

As of 23 August 2026, this Paper Citation Record lists 40 of 40 outbound references and 0 inbound Pith citation observations for arXiv:2605.06355.

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

pith.paper-citation-record.v1
2605.06355 v2

Coverage vector

measured 40 of 40 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-06-30T23:25:51.272306Z

measured 40 of 40 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-23T06:30:58.430688+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

40 of 40 outbound references displayed

verified exact1
verified fuzzy39
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation e218126d-cf87-4a94-8523-e13e8ee319bf · outbound

This paper cites Rethinking the diffusion models for missing data imputation: A gradient flow perspective.Advances in Neural Information Processing Systems, 37:112050–112103.

Order-Agnostic Autoregressive Modelling with Missing Data Rethinking the diffusion models for missing data imputation: A gradient flow perspective.Advances in Neural Information Processing Systems, 37:112050–112103

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T11:13:41.369456Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation b3115926-3cc0-4b88-8484-a2232d8cc16b · outbound

This paper cites UCI machine learning repository.

Order-Agnostic Autoregressive Modelling with Missing Data UCI machine learning repository

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T11:13:41.354997Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation a8bd0943-4607-47a3-a8a9-5eaa794ac937 · outbound

This paper cites Generative adversarial nets.Advances in neural information processing systems, 27.

Order-Agnostic Autoregressive Modelling with Missing Data Generative adversarial nets.Advances in neural information processing systems, 27

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T11:13:41.337665Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation ecddfd12-12a8-4367-8d5c-079dee38f1f1 · outbound

This paper cites Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio.

Order-Agnostic Autoregressive Modelling with Missing Data Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T11:13:41.341339Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 6d1edfdb-1239-4a55-8a19-f32a326fb686 · outbound

This paper cites Denoising diffusion probabilistic models.Advances in neural information processing systems, 33:6840–6851.

Order-Agnostic Autoregressive Modelling with Missing Data Denoising diffusion probabilistic models.Advances in neural information processing systems, 33:6840–6851

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T11:13:41.415297Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 6e761bf9-a834-4c22-ac49-62fd946c17c8 · outbound

This paper cites Gritsenko, Jasmijn Bastings, Ben Poole, Rianne van den Berg, and Tim Salimans.

Order-Agnostic Autoregressive Modelling with Missing Data Gritsenko, Jasmijn Bastings, Ben Poole, Rianne van den Berg, and Tim Salimans

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T11:13:41.436979Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation f334d13c-245d-4186-b499-ae95c2ab1ef6 · outbound

This paper cites Active feature acquisition with supervised matrix completion.

Order-Agnostic Autoregressive Modelling with Missing Data Active feature acquisition with supervised matrix completion

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T11:13:41.348332Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 69e2033f-f614-41d2-b6b1-dca823a9f10a · outbound

This paper cites Optimal design of experiments with anticipated pattern of missing observations.Journal of theoretical biology, 228(2):251–260.

Order-Agnostic Autoregressive Modelling with Missing Data Optimal design of experiments with anticipated pattern of missing observations.Journal of theoretical biology, 228(2):251–260

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T11:13:41.409754Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 53b352a7-3239-4569-a807-d24eca75a27c · outbound

This paper cites not-miwae: Deep generative modelling with missing not at random data.

Order-Agnostic Autoregressive Modelling with Missing Data not-miwae: Deep generative modelling with missing not at random data

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T11:13:41.343136Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation c5935a24-dc50-4622-b12c-2e9087a3d4ab · outbound

This paper cites Variational autoencoder with arbitrary conditioning.

Order-Agnostic Autoregressive Modelling with Missing Data Variational autoencoder with arbitrary conditioning

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T11:13:41.339340Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 95e4db3b-a7e9-42cd-a49b-3a218f8cc245 · outbound

This paper cites Hyperimpute: Generalized iterative imputation with automatic model selection.

Order-Agnostic Autoregressive Modelling with Missing Data Hyperimpute: Generalized iterative imputation with automatic model selection

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T11:13:41.352465Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 9a722eaf-19c9-49b3-8122-05609897674a · outbound

This paper cites The analysis of designed experiments with missing observations.Journal of the Royal Statistical Society: Series C (Applied Statistics), 27(1):38–46.

Order-Agnostic Autoregressive Modelling with Missing Data The analysis of designed experiments with missing observations.Journal of the Royal Statistical Society: Series C (Applied Statistics), 27(1):38–46

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T11:13:41.412568Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 2fede397-71b1-4624-a05e-d629e99cc667 · outbound

This paper cites Auto-Encoding Variational Bayes.

Order-Agnostic Autoregressive Modelling with Missing Data Auto-Encoding Variational Bayes

Reference 13

Resolution: verified exact; local_arxiv, observed 2026-07-01T13:25:44.756649Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 5b4decee-f691-4efe-ac59-0faf82d72df0 · outbound

This paper cites Improved variational inference with inverse autoregressive flow.Advances in neural information processing systems, 29.

Order-Agnostic Autoregressive Modelling with Missing Data Improved variational inference with inverse autoregressive flow.Advances in neural information processing systems, 29

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T11:13:41.417392Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 5d34e8f4-a252-40f7-bb7d-cfbe12f488ab · outbound

This paper cites Estimating mutual information.

Order-Agnostic Autoregressive Modelling with Missing Data Estimating mutual information

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T11:13:41.394932Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 99f5a54f-c77b-4a15-a876-dcef97b58aef · outbound

This paper cites Learning from incomplete data with generative adversarial networks.

Order-Agnostic Autoregressive Modelling with Missing Data Learning from incomplete data with generative adversarial networks

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T11:13:41.371650Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 9b54b567-5e92-4aac-b320-229186a5e569 · outbound

This paper cites Learning from irregularly-sampled time series: A missing data perspective.

Order-Agnostic Autoregressive Modelling with Missing Data Learning from irregularly-sampled time series: A missing data perspective

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T11:13:41.392899Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 9e447686-f401-4e87-9679-cf607d15c7d9 · outbound

This paper cites Exploiting missing clinical data in bayesian network modeling for predicting medical problems.Journal of biomedical informatics, 41(1):1–14.

Order-Agnostic Autoregressive Modelling with Missing Data Exploiting missing clinical data in bayesian network modeling for predicting medical problems.Journal of biomedical informatics, 41(1):1–14

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T11:13:41.434884Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation f150d342-29cc-4bc8-881f-1418b365bc18 · outbound

This paper cites John Wiley & Sons.

Order-Agnostic Autoregressive Modelling with Missing Data John Wiley & Sons

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T11:13:41.430889Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 90070e58-2306-4a4a-b835-3dc6fb291dfa · outbound

This paper cites Deep Learning Face Attributes in the Wild.

Order-Agnostic Autoregressive Modelling with Missing Data Deep Learning Face Attributes in the Wild

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T11:13:41.390623Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 9f9bf97b-b6ce-42a9-a3d6-d5927e1a92c3 · outbound

This paper cites Repaint: Inpainting using denoising diffusion probabilistic models.

Order-Agnostic Autoregressive Modelling with Missing Data Repaint: Inpainting using denoising diffusion probabilistic models

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T11:13:41.425341Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation bd6a67e7-8fda-4ef3-8869-101e6d3d871f · outbound

This paper cites Eddi: Efficient dynamic discovery of high-value information with partial vae.

Order-Agnostic Autoregressive Modelling with Missing Data Eddi: Efficient dynamic discovery of high-value information with partial vae

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T11:13:41.427755Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 9772222d-a44a-4da3-8dc8-441d240ea296 · outbound

This paper cites Vaem: a deep generative model for heterogeneous mixed type data.Advances in Neural Information Processing Systems, 33:11237–11247.

Order-Agnostic Autoregressive Modelling with Missing Data Vaem: a deep generative model for heterogeneous mixed type data.Advances in Neural Information Processing Systems, 33:11237–11247

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T11:13:41.388061Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 95364559-7f9b-4d4a-91dd-46277004bb1e · outbound

This paper cites Miwae: Deep generative modelling and imputation of incomplete data sets.

Order-Agnostic Autoregressive Modelling with Missing Data Miwae: Deep generative modelling and imputation of incomplete data sets

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T11:13:41.363533Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation c2a5741f-9924-44dc-883f-fbef8b6f4f23 · outbound

This paper cites Active feature- value acquisition for classifier induction.

Order-Agnostic Autoregressive Modelling with Missing Data Active feature- value acquisition for classifier induction

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T11:13:41.376597Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation fa80462a-50df-4d38-96d1-12bd4fbc2500 · outbound

This paper cites Handling incomplete heterogeneous data using vaes.Pattern Recognition, 107:107501.

Order-Agnostic Autoregressive Modelling with Missing Data Handling incomplete heterogeneous data using vaes.Pattern Recognition, 107:107501

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T11:13:41.380566Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation f5386286-544e-4495-a0b9-e454c4e24e9b · outbound

This paper cites Normalizing flows for probabilistic modeling and inference.Journal of Machine Learning Research, 22(57):1–64.

Order-Agnostic Autoregressive Modelling with Missing Data Normalizing flows for probabilistic modeling and inference.Journal of Machine Learning Research, 22(57):1–64

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T11:13:41.374012Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 9f1b8e85-6d70-4bf6-b183-3f70394c2f01 · outbound

This paper cites Missing data imputation and acquisition with deep hierarchical models and hamiltonian monte carlo.Advances in Neural Information Processing Systems, 35:35839–35851.

Order-Agnostic Autoregressive Modelling with Missing Data Missing data imputation and acquisition with deep hierarchical models and hamiltonian monte carlo.Advances in Neural Information Processing Systems, 35:35839–35851

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T11:13:41.383104Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 8012d685-5a7a-4473-b912-49cce1010dd3 · outbound

This paper cites Mcflow: Monte carlo flow models for data imputation.

Order-Agnostic Autoregressive Modelling with Missing Data Mcflow: Monte carlo flow models for data imputation

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T11:13:41.396969Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 865e8d03-c9d6-404e-9da8-74275a6eed4e · outbound

This paper cites Active feature-value acquisition.

Order-Agnostic Autoregressive Modelling with Missing Data Active feature-value acquisition

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T11:13:41.385540Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 64983208-9fd0-4f11-80cd-05235181c306 · outbound

This paper cites Denoising diffusion implicit models.

Order-Agnostic Autoregressive Modelling with Missing Data Denoising diffusion implicit models

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T11:13:41.344899Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 824256fd-b310-4839-a7ca-ddddd4beedf8 · outbound

This paper cites Missforest—non-parametric missing value imputation for mixed-type data.Bioinformatics, 28(1):112–118.

Order-Agnostic Autoregressive Modelling with Missing Data Missforest—non-parametric missing value imputation for mixed-type data.Bioinformatics, 28(1):112–118

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T11:13:41.334182Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 2ac33857-cc0a-4bc1-beea-8312f74595a4 · outbound

This paper cites Multiple imputation for missing data in epidemiological and clinical research: potential and pitfalls.Bmj, 338.

Order-Agnostic Autoregressive Modelling with Missing Data Multiple imputation for missing data in epidemiological and clinical research: potential and pitfalls.Bmj, 338

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T11:13:41.335923Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation c37cd2f0-0057-4032-89cb-7de489564375 · outbound

This paper cites Csdi: Conditional score-based diffusion models for probabilistic time series imputation.

Order-Agnostic Autoregressive Modelling with Missing Data Csdi: Conditional score-based diffusion models for probabilistic time series imputation

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T11:13:41.399062Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 0e1bc80d-bdbf-4dcc-9ad6-34cb21f958a1 · outbound

This paper cites Neural autoregressive distribution estimation.Journal of Machine Learning Research, 17(205):1–37.

Order-Agnostic Autoregressive Modelling with Missing Data Neural autoregressive distribution estimation.Journal of Machine Learning Research, 17(205):1–37

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T11:13:41.366220Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 7f7e2df5-ecd0-426c-9961-4ba1c9f46a69 · outbound

This paper cites A deep and tractable density estimator.

Order-Agnostic Autoregressive Modelling with Missing Data A deep and tractable density estimator

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T11:13:41.419522Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 121becdd-3eb4-4fb7-8490-7c3cccd9f0fd · outbound

This paper cites mice: Multivariate imputation by chained equations in r.Journal of statistical software, 45:1–67.

Order-Agnostic Autoregressive Modelling with Missing Data mice: Multivariate imputation by chained equations in r.Journal of statistical software, 45:1–67

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T11:13:41.422258Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation fd02e17e-1ad0-4d41-ac26-04992a0918ab · outbound

This paper cites Learning-order autoregressive models with application to molecular graph generation.

Order-Agnostic Autoregressive Modelling with Missing Data Learning-order autoregressive models with application to molecular graph generation

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T11:13:41.401887Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 7e688a48-7422-4f41-a803-957ecb0e40bb · outbound

This paper cites Gain: Missing data imputation using generative adversarial nets.

Order-Agnostic Autoregressive Modelling with Missing Data Gain: Missing data imputation using generative adversarial nets

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T11:13:41.404224Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 323693ae-0006-4ea5-85b3-4de6ccf5fce4 · outbound

This paper cites logistic model with input masked by MCAR.

Order-Agnostic Autoregressive Modelling with Missing Data logistic model with input masked by MCAR

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T11:13:41.406730Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Pith citing papers

No inbound Pith citation observations are available.