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Paper Citation Record · LEDGER

Distributionally Faithful Imputation via Positive Semi-Definite Kernel Density Estimation

As of 15 August 2026, this Paper Citation Record lists 40 of 40 outbound references and 0 inbound Pith citation observations for arXiv:2607.07767.

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

pith.paper-citation-record.v1
2607.07767 v1

Coverage vector

measured 40 of 40 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-07-10T18:44:34.040973Z

measured 40 of 40 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+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

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  • verified fuzzy31
  • unresolved2
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 3a9e96e4-9cda-4966-8cb7-6d4cadc43ee6 · outbound

This paper cites Springer Science & Business Media.

Distributionally Faithful Imputation via Positive Semi-Definite Kernel Density Estimation Springer Science & Business Media

Reference 1

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Observation c0f9e20f-ebae-444c-8054-593b0b4954d2 · outbound

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Distributionally Faithful Imputation via Positive Semi-Definite Kernel Density Estimation Unresolved cited work

Reference 2

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Source-reported events for the cited work

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Observation b9392074-e32b-49d1-8a29-96a603310a18 · outbound

This paper cites A note on reverse pinsker inequalities.IEEE transactions on information theory, 65(7):4094–4096, 2019.

Distributionally Faithful Imputation via Positive Semi-Definite Kernel Density Estimation A note on reverse pinsker inequalities.IEEE transactions on information theory, 65(7):4094–4096, 2019

Reference 3

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Observation fe69dbbc-1e15-4739-a853-2499b11a5c5b · outbound

This paper cites Cambridge University Press.

Distributionally Faithful Imputation via Positive Semi-Definite Kernel Density Estimation Cambridge University Press

Reference 4

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 686bd41f-5321-4c9f-8cad-db2f5428c7b4 · outbound

This paper cites Alternating minimization as sequential unconstrained minimization: a survey.

Distributionally Faithful Imputation via Positive Semi-Definite Kernel Density Estimation Alternating minimization as sequential unconstrained minimization: a survey

Reference 5

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation c20caae3-5851-4819-9d1d-423995a8de1b · outbound

This paper cites John Wiley & Sons, 1999.

Distributionally Faithful Imputation via Positive Semi-Definite Kernel Density Estimation John Wiley & Sons, 1999

Reference 6

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation c5d01222-2431-420e-85b7-f0c2ca30df23 · outbound

This paper cites I-divergence geometry of probability distributions and minimization problems.

Distributionally Faithful Imputation via Positive Semi-Definite Kernel Density Estimation I-divergence geometry of probability distributions and minimization problems

Reference 7

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation f115ce05-669c-4c21-b4f3-7e485b08ae5d · outbound

This paper cites Maximum likelihood from incomplete data via the em algorithm.Journal of the Royal Statistical Society: Series B (Methodological), 39(1):1–38, 1977.

Distributionally Faithful Imputation via Positive Semi-Definite Kernel Density Estimation Maximum likelihood from incomplete data via the em algorithm.Journal of the Royal Statistical Society: Series B (Methodological), 39(1):1–38, 1977

Reference 8

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation ea1ac94d-0a61-49f8-899c-ce7e9aeabc43 · outbound

This paper cites Matrix completion and low-rank svd via fast alternating least squares.Journal of Machine Learning Research, 16:3367–3402, 2015.

Distributionally Faithful Imputation via Positive Semi-Definite Kernel Density Estimation Matrix completion and low-rank svd via fast alternating least squares.Journal of Machine Learning Research, 16:3367–3402, 2015

Reference 9

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 32145054-8bd9-4686-aec3-294016777716 · outbound

This paper cites On the consistency of supervised learning with missing values.Statistical Papers, 65(9):5447–5479, 2024.

Distributionally Faithful Imputation via Positive Semi-Definite Kernel Density Estimation On the consistency of supervised learning with missing values.Statistical Papers, 65(9):5447–5479, 2024

Reference 10

Resolution
verified fuzzy
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Source-reported events for the cited work

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Observation 4e0e677d-5e73-4d00-9f50-b5a81ee76051 · outbound

This paper cites Regularization techniques for learning with matrices.The Journal of Machine Learning Research, 13(1):1865–1890, 2012.

Distributionally Faithful Imputation via Positive Semi-Definite Kernel Density Estimation Regularization techniques for learning with matrices.The Journal of Machine Learning Research, 13(1):1865–1890, 2012

Reference 11

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation b13c4924-150e-4670-8fb1-b05d70c4baf4 · outbound

This paper cites Kingma and Jimmy Ba.

Distributionally Faithful Imputation via Positive Semi-Definite Kernel Density Estimation Kingma and Jimmy Ba

Reference 12

Resolution
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Source-reported events for the cited work

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Observation 1680f931-638a-4ddd-b4df-a7c50dcb1679 · outbound

This paper cites Imputation for prediction: beware of diminishing returns.

Distributionally Faithful Imputation via Positive Semi-Definite Kernel Density Estimation Imputation for prediction: beware of diminishing returns

Reference 13

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Source-reported events for the cited work

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Observation 05d63c97-2cec-4e04-99e7-3a50a3db57dd · outbound

This paper cites John Wiley and Sons, 3 edition, 2019.

Distributionally Faithful Imputation via Positive Semi-Definite Kernel Density Estimation John Wiley and Sons, 3 edition, 2019

Reference 14

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 52101ff5-201d-436f-87f2-a1d0d25651cc · outbound

This paper cites Explicit and recursive estimates of the Lambert W function.

Distributionally Faithful Imputation via Positive Semi-Definite Kernel Density Estimation Explicit and recursive estimates of the Lambert W function

Reference 15

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 4e92cd83-db34-40b6-9791-ed8cbc8307c8 · outbound

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

Distributionally Faithful Imputation via Positive Semi-Definite Kernel Density Estimation Vaem: a deep generative model for heterogeneous mixed type data.Advances in Neural Information Processing Systems, 33:11237–11247

Reference 16

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation de1e42ef-fd74-49ca-8736-14fcbe1a500a · outbound

This paper cites Non-parametric models for non- negative functions.Advances in neural information processing systems, 33:12816–12826, 2020.

Distributionally Faithful Imputation via Positive Semi-Definite Kernel Density Estimation Non-parametric models for non- negative functions.Advances in neural information processing systems, 33:12816–12826, 2020

Reference 17

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 1d00fb79-2b4e-4c85-b6e2-f96abadf4859 · outbound

This paper cites Second order conditions to decom- pose smooth functions as sums of squares.SIAM Journal on Optimization, 34(1):616–641, 2024.

Distributionally Faithful Imputation via Positive Semi-Definite Kernel Density Estimation Second order conditions to decom- pose smooth functions as sums of squares.SIAM Journal on Optimization, 34(1):616–641, 2024

Reference 18

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation e76f325a-7a24-4770-9aac-bc08d40c4a39 · outbound

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Distributionally Faithful Imputation via Positive Semi-Definite Kernel Density Estimation Unresolved cited work

Reference 19

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation ac9ede25-0def-4faf-880d-d08bdda3dfb3 · outbound

This paper cites Missing data imputation using optimal transport.

Distributionally Faithful Imputation via Positive Semi-Definite Kernel Density Estimation Missing data imputation using optimal transport

Reference 20

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 1afd1079-698c-48d0-abe3-1d7dbc4b3a2a · outbound

This paper cites SIAM, 1994.

Distributionally Faithful Imputation via Positive Semi-Definite Kernel Density Estimation SIAM, 1994

Reference 21

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verified fuzzy
raw_fallback, observed 2026-07-10T18:47:31.784180Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation cf4c4da1-6318-4243-9a9f-30fcf5613b16 · outbound

This paper cites N¨ af, E.

Distributionally Faithful Imputation via Positive Semi-Definite Kernel Density Estimation N¨ af, E

Reference 22

Resolution
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arxiv_id, observed 2026-07-10T18:47:31.526972Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 81582d66-805e-498d-af99-d1bc83334888 · outbound

This paper cites Imputation scores.The Annals of Applied Statistics, 17(3):2452–2472, 2023.

Distributionally Faithful Imputation via Positive Semi-Definite Kernel Density Estimation Imputation scores.The Annals of Applied Statistics, 17(3):2452–2472, 2023

Reference 23

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verified fuzzy
raw_fallback, observed 2026-07-10T18:47:31.785997Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-07-10T18:44:34.040973Z digest=sha256:d9477cd0c80cbf4dc1ce9ae0d012b7b294d3c67dba8a8bc3d2dce5022a225ab6

Observation 62b220bb-bad7-4a83-bd3b-f05a28dabea7 · outbound

This paper cites Multivariate beta distributions and independence properties of the wishart distribution.The Annals of Mathematical Statistics, pages 261–269, 1964.

Distributionally Faithful Imputation via Positive Semi-Definite Kernel Density Estimation Multivariate beta distributions and independence properties of the wishart distribution.The Annals of Mathematical Statistics, pages 261–269, 1964

Reference 24

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verified fuzzy
raw_fallback, observed 2026-07-10T18:47:31.782481Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 3056ee98-e391-4671-a100-bba6462de1f0 · outbound

This paper cites Scikit- learn: Machine learning in python.the Journal of machine Learning research, 12:2825–2830, 2011.

Distributionally Faithful Imputation via Positive Semi-Definite Kernel Density Estimation Scikit- learn: Machine learning in python.the Journal of machine Learning research, 12:2825–2830, 2011

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-07-10T18:47:31.780676Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 0894dc14-c619-468f-863a-431dff62ebab · outbound

This paper cites Psd representations for effective probability models.

Distributionally Faithful Imputation via Positive Semi-Definite Kernel Density Estimation Psd representations for effective probability models

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-07-10T18:47:31.788077Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 21c31a4f-7e23-4f85-9b64-eb81a4a19aa7 · outbound

This paper cites Finding Global Minima via Kernel Approximations.

Distributionally Faithful Imputation via Positive Semi-Definite Kernel Density Estimation Finding Global Minima via Kernel Approximations

Reference 27

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verified exact
local_arxiv, observed 2026-07-10T18:47:31.531940Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 2a9d3cfa-c247-4647-bd69-b80970a1ef01 · outbound

This paper cites Cambridge University Press.

Distributionally Faithful Imputation via Positive Semi-Definite Kernel Density Estimation Cambridge University Press

Reference 28

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verified fuzzy
raw_fallback, observed 2026-07-10T18:47:31.766182Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 351c1e79-b6dc-4bfc-bb81-f9157532e993 · outbound

This paper cites Sparse gaussian processes using pseudo-inputs.

Distributionally Faithful Imputation via Positive Semi-Definite Kernel Density Estimation Sparse gaussian processes using pseudo-inputs

Reference 29

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verified fuzzy
raw_fallback, observed 2026-07-10T18:47:31.748457Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation e4feec1b-2e9a-4036-b908-3881fcc8e434 · outbound

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

Distributionally Faithful Imputation via Positive Semi-Definite Kernel Density Estimation Missforest—non-parametric missing value imputation for mixed-type data.Bioinformatics, 28(1):112–118

Reference 30

Resolution
verified fuzzy
raw_fallback, observed 2026-07-10T18:47:31.746364Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-07-10T18:44:34.040973Z digest=sha256:193dba71cf9f1cff858a2313da5da0c38c550327e6b014558973d289c901ea1b

Observation 41d75d66-9da9-47cb-bf0d-e4e437033858 · outbound

This paper cites The energy of data.Annual Review of Statistics and Its Application, 4(1):447–479, 2017.

Distributionally Faithful Imputation via Positive Semi-Definite Kernel Density Estimation The energy of data.Annual Review of Statistics and Its Application, 4(1):447–479, 2017

Reference 31

Resolution
verified fuzzy
raw_fallback, observed 2026-07-10T18:47:31.750641Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-07-10T18:44:34.040973Z digest=sha256:6b16434b6b1262a7cae2778b0144b593df90cce6f22aa8a12536ddbc44936093

Observation 3d57c542-74d5-4e86-982c-d72d5f70a99b · outbound

This paper cites Csdi: Conditional score-based diffusion models for probabilistic time series imputation.Advances in Neural Information Processing Systems, 34:24804–24816.

Distributionally Faithful Imputation via Positive Semi-Definite Kernel Density Estimation Csdi: Conditional score-based diffusion models for probabilistic time series imputation.Advances in Neural Information Processing Systems, 34:24804–24816

Reference 32

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verified fuzzy
raw_fallback, observed 2026-07-10T18:47:31.754591Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 65477071-9bd4-4571-b5dc-5847abbd4a94 · outbound

This paper cites Tsybakov.Introduction to Nonparametric Estimation.

Distributionally Faithful Imputation via Positive Semi-Definite Kernel Density Estimation Tsybakov.Introduction to Nonparametric Estimation

Reference 33

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verified fuzzy
raw_fallback, observed 2026-07-10T18:47:31.756352Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-07-10T18:44:34.040973Z digest=sha256:f6b0ca337f1d6e38d98e28834e0b1302a97ed93c1eb87ccbf722be47c76bb1a8

Observation b2f7f0e5-0faf-4fd4-8a2a-cbd2a7ad9d9c · outbound

This paper cites mice: Multivariate imputation by chained equations in r.Journal of Statistical Software, 45(3):1–67, 2011.

Distributionally Faithful Imputation via Positive Semi-Definite Kernel Density Estimation mice: Multivariate imputation by chained equations in r.Journal of Statistical Software, 45(3):1–67, 2011

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-07-10T18:47:31.758445Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-07-10T18:44:34.040973Z digest=sha256:38abb0c8ff2fb1067147d75846cac93af7027c4d55e7585491179ef5dc8a46a4

Observation 1f4737e7-1751-43c9-897d-c6e7511e4e23 · outbound

This paper cites Springer.

Distributionally Faithful Imputation via Positive Semi-Definite Kernel Density Estimation Springer

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-07-10T18:47:31.762247Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-07-10T18:44:34.040973Z digest=sha256:1384feb5bc34408d28d6aa5eb88bd1e0ff43be911284b6b393857eb89c951f7e

Observation 6a60366e-9658-4431-866d-1efd6bf68ae8 · outbound

This paper cites Are deep learning models superior for missing data imputation in large surveys? Evidence from an empirical comparison.

Distributionally Faithful Imputation via Positive Semi-Definite Kernel Density Estimation Are deep learning models superior for missing data imputation in large surveys? Evidence from an empirical comparison

Reference 36

Resolution
verified exact
local_arxiv, observed 2026-07-10T18:47:31.523489Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-07-10T18:44:34.040973Z digest=sha256:7af7a866aefa4e726a6034e23e08b3de8fda55bba7257d0163f0ca0364eb6cef

Observation 7d5351d0-6166-4754-8eb6-57388c429533 · outbound

This paper cites Numerical optimization, 2006.

Distributionally Faithful Imputation via Positive Semi-Definite Kernel Density Estimation Numerical optimization, 2006

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-07-10T18:47:31.760366Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-07-10T18:44:34.040973Z digest=sha256:ae79963da4f7ed94a4c95a5b3897f778d9ab64c14412693b193e86e0b90226e1

Observation 1dc577e0-dbc7-4874-991c-f653f0f496e4 · outbound

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

Distributionally Faithful Imputation via Positive Semi-Definite Kernel Density Estimation Gain: Missing data imputation using generative adversarial nets

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-07-10T18:47:31.737850Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-07-10T18:44:34.040973Z digest=sha256:51f034f67996e722bf0c0a40c9fb9eff077f96d038c02fde0a1acdfd486c9dc9

Observation 5fafeb48-df56-48b2-b41c-66faf672a58f · outbound

This paper cites Our methodPSD_Imputeappears as a conditional mean estimator psd_mean and as a multiple imputer psd_multiple with m= 10 draws.

Distributionally Faithful Imputation via Positive Semi-Definite Kernel Density Estimation Our methodPSD_Imputeappears as a conditional mean estimator psd_mean and as a multiple imputer psd_multiple with m= 10 draws

Reference 39

Resolution
malformed identifier
raw_fallback, observed 2026-07-10T18:47:31.770701Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-07-10T18:44:34.040973Z digest=sha256:aec68d39930bbf0cf287221e1f956f42d4a141b47d86d407422f06e630e7a3a8

Observation 32f303c4-2ca1-4399-bece-b4f76475aff1 · outbound

This paper cites 2.fort= 0,1,.

Distributionally Faithful Imputation via Positive Semi-Definite Kernel Density Estimation 2.fort= 0,1,

Reference 40

Resolution
malformed identifier
raw_fallback, observed 2026-07-10T18:47:31.774777Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-07-10T18:44:34.040973Z digest=sha256:736b845616fecabd4d8a95b9badab07eb646a1c68befc00dee39f7ec4c105127

Pith citing papers

No inbound Pith citation observations are available.