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Paper Citation Record · LEDGER

Learning High-dimensional Gaussians from Censored Data

As of 19 August 2026, this Paper Citation Record lists 100 of 102 outbound references and 2 inbound Pith citation observations for arXiv:2504.19446.

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

pith.paper-citation-record.v1
2504.19446 v1

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measured 100 of 102 reference resolution

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measured 102 of 102 standing notices

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measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-30T23:25:55.375541Z

measured 0 of 1 external citation measurements

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Source: arxiv_reference, observed 2026-06-30T23:35:08.049455Z

Reference resolution

100 of 102 outbound references displayed

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External citation measurements

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Outbound references

Observation 64e0c489-e5e3-4420-8095-0bc08df80e78 · outbound

This paper cites Statistical methods in medical research.

Learning High-dimensional Gaussians from Censored Data Statistical methods in medical research

Reference 1

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Observation 768fd602-597e-43b7-b587-5f799e8343c2 · outbound

This paper cites Classification of alcohols obtained by qcm sensors with different characteristics using abc based neural network.

Learning High-dimensional Gaussians from Censored Data Classification of alcohols obtained by qcm sensors with different characteristics using abc based neural network

Reference 2

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Observation 847c454a-c24f-48af-a055-bb4c9ddd6d6d · outbound

This paper cites Multiple imputation for missing data: A cautionary tale.

Learning High-dimensional Gaussians from Censored Data Multiple imputation for missing data: A cautionary tale

Reference 3

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This paper cites Regression analysis when the dependent variable is truncated normal.

Learning High-dimensional Gaussians from Censored Data Regression analysis when the dependent variable is truncated normal

Reference 4

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Observation 3d54d9d3-4a86-4f7c-9903-2d2504be06a4 · outbound

This paper cites Regression models: Censored, sample selected, or truncated data , volume 111.

Learning High-dimensional Gaussians from Censored Data Regression models: Censored, sample selected, or truncated data , volume 111

Reference 5

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This paper cites Multiple regression and estimation of the mean of a multivariate normal distribution.

Learning High-dimensional Gaussians from Censored Data Multiple regression and estimation of the mean of a multivariate normal distribution

Reference 6

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This paper cites The art of progressive censoring.

Learning High-dimensional Gaussians from Censored Data The art of progressive censoring

Reference 7

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This paper cites Robustly learning mixtures of k arbitrary gaussians.

Learning High-dimensional Gaussians from Censored Data Robustly learning mixtures of k arbitrary gaussians

Reference 8

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Observation 77822f78-12ea-4a88-92b7-7bda4dd6b69e · outbound

This paper cites Sampling from a log-concave distribution with projected langevin monte carlo.

Learning High-dimensional Gaussians from Censored Data Sampling from a log-concave distribution with projected langevin monte carlo

Reference 9

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This paper cites Handling missing data in survey research.

Learning High-dimensional Gaussians from Censored Data Handling missing data in survey research

Reference 10

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This paper cites Maximum likelihood estimation of the multivariate normal mixture model.

Learning High-dimensional Gaussians from Censored Data Maximum likelihood estimation of the multivariate normal mixture model

Reference 11

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This paper cites Identification in missing data models represented by directed acyclic graphs.

Learning High-dimensional Gaussians from Censored Data Identification in missing data models represented by directed acyclic graphs

Reference 12

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Learning High-dimensional Gaussians from Censored Data Mean and variance of truncated normal distributions

Reference 13

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This paper cites Polynomial learning of distribution families.

Learning High-dimensional Gaussians from Censored Data Polynomial learning of distribution families

Reference 14

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This paper cites Double/debiased machine learning for treatment and structural parameters, 2018.

Learning High-dimensional Gaussians from Censored Data Double/debiased machine learning for treatment and structural parameters, 2018

Reference 15

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Learning High-dimensional Gaussians from Censored Data Rethinking the truncated normal distribution

Reference 16

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This paper cites High-dimensional robust mean estimation via gradient descent.

Learning High-dimensional Gaussians from Censored Data High-dimensional robust mean estimation via gradient descent

Reference 17

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This paper cites What Makes A Good Fisherman? Linear Regression under Self-Selection Bias.

Learning High-dimensional Gaussians from Censored Data What Makes A Good Fisherman? Linear Regression under Self-Selection Bias

Reference 18

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Learning High-dimensional Gaussians from Censored Data What makes a good fisherman? linear regression under self-selection bias

Reference 19

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Learning High-dimensional Gaussians from Censored Data Learning mixtures of structured distributions over discrete domains

Reference 20

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Learning High-dimensional Gaussians from Censored Data Missing not at random in end of life care studies: multiple imputation and sensitivity analysis on data from the action study

Reference 21

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Learning High-dimensional Gaussians from Censored Data List decodable mean estimation in nearly linear time

Reference 22

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Learning High-dimensional Gaussians from Censored Data De-Biased Machine Learning of Global and Local Parameters Using Regularized Riesz Representers

Reference 23

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Learning High-dimensional Gaussians from Censored Data A Simple and General Debiased Machine Learning Theorem with Finite Sample Guarantees

Reference 24

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Learning High-dimensional Gaussians from Censored Data On the solution of estimating equations for truncated and censored samples from normal populations

Reference 25

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Learning High-dimensional Gaussians from Censored Data Truncated and censored samples: theory and applications

Reference 26

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Learning High-dimensional Gaussians from Censored Data Learning from untrusted data

Reference 27

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Learning High-dimensional Gaussians from Censored Data Learning mixtures of gaussians

Reference 28

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Learning High-dimensional Gaussians from Censored Data Efficient statistics, in high dimensions, from truncated samples

Reference 29

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Learning High-dimensional Gaussians from Censored Data Computationally and statistically efficient truncated regression

Reference 30

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Learning High-dimensional Gaussians from Censored Data Robustly Learning any Clusterable Mixture of Gaussians

Reference 31

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Learning High-dimensional Gaussians from Censored Data Simplified estimation from censored normal samples

Reference 32

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Learning High-dimensional Gaussians from Censored Data Estimation of parameters of truncated or censored exponential distributions

Reference 33

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Learning High-dimensional Gaussians from Censored Data Recent Advances in Algorithmic High-Dimensional Robust Statistics

Reference 34

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Learning High-dimensional Gaussians from Censored Data Robustly learning a gaussian: Getting optimal error, efficiently

Reference 35

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Learning High-dimensional Gaussians from Censored Data Robust estimators in high-dimensions without the computational intractability

Reference 36

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Learning High-dimensional Gaussians from Censored Data Statistical query lower bounds for learning truncated gaussians

Reference 37

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Learning High-dimensional Gaussians from Censored Data A statistical taylor theorem and extrapolation of truncated densities

Reference 38

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-16T06:04:35.617660Z digest=sha256:2d62865120be356bce3174aad7de5ce377aecc9830ebceafc20ecc05e39cb69f

Observation ae5eaa3b-7e8d-47a4-950b-53b8bc423c04 · outbound

This paper cites Detecting low-degree truncation.

Learning High-dimensional Gaussians from Censored Data Detecting low-degree truncation

Reference 39

Resolution
verified fuzzy
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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-16T06:04:35.621056Z digest=sha256:cbcb1cb54f9f6f4d1d419fb32576962f5b5130720f7165ccb3f4d64a4480b029

Observation 0e4deb7b-947d-417d-9300-f428bf05386d · outbound

This paper cites Maximum likelihood from incomplete data via the em algorithm.

Learning High-dimensional Gaussians from Censored Data Maximum likelihood from incomplete data via the em algorithm

Reference 40

Resolution
verified fuzzy
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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-16T06:04:35.624792Z digest=sha256:a9c33c633f3180878be0a23e5972b292f80f731c837c99a4e81a3dfa2a1177e5

Observation 8a788a7e-297f-4f6a-a2b1-c4ed4acc224b · outbound

This paper cites Testing convex truncation.

Learning High-dimensional Gaussians from Censored Data Testing convex truncation

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T06:04:36.695906Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-16T06:04:35.628322Z digest=sha256:92a06d13fe6e6d09102a1420bbdf55b07a180fdf54621acfbed6c08057b27985

Observation b12504ea-c3c1-448b-9cda-7158f9aec958 · outbound

This paper cites Truncated linear regression in high dimensions.

Learning High-dimensional Gaussians from Censored Data Truncated linear regression in high dimensions

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T06:04:36.684400Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-16T06:04:35.631799Z digest=sha256:d985f8b6f92190fe53c83c4fe0a47e98f1332f62e5cce3dc648d2c2b71733102

Observation 63993ed2-2a2c-4604-b349-e019ac7f0446 · outbound

This paper cites Efficient truncated linear regression with unknown noise variance.

Learning High-dimensional Gaussians from Censored Data Efficient truncated linear regression with unknown noise variance

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T06:04:36.672288Z

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-16T06:04:35.635625Z digest=sha256:cdcb119057c01a81be375cf4ddecdd4d0ad13b4d5f42dba671a419ecc37328ab

Observation 3eac1f19-d8cd-4a82-bca3-e568aedb2745 · outbound

This paper cites The relative performance of full information maximum likelihood estimation for missing data in structural equation models.

Learning High-dimensional Gaussians from Censored Data The relative performance of full information maximum likelihood estimation for missing data in structural equation models

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T06:04:36.660078Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-16T06:04:35.639305Z digest=sha256:747e78146366be196112545ede41f78841e1df7b9df8944b7433e1b562149140

Observation 5ab87490-b443-444a-8502-037627dc6ce0 · outbound

This paper cites Properties and applications of hh functions.

Learning High-dimensional Gaussians from Censored Data Properties and applications of hh functions

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T06:04:36.647129Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-16T06:04:35.643401Z digest=sha256:caf3c6784ea335d972ab3f51572a5550831151a017cd74a1731e4083998407a5

Observation c15004e7-974d-4887-abcd-f40e38424d75 · outbound

This paper cites Efficient parameter estimation of truncated boolean product distributions.

Learning High-dimensional Gaussians from Censored Data Efficient parameter estimation of truncated boolean product distributions

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T06:04:36.635601Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-16T06:04:35.647615Z digest=sha256:a660f346a81e7a92ab72aaf7887fb05dcdcb41dcbe433ab605a5b8bf6595c034

Observation db36565a-c22c-4aaf-9ddc-e1a9836bcb61 · outbound

This paper cites An examination into the registered speeds of american trotting horses, with remarks on their value as hereditary data.

Learning High-dimensional Gaussians from Censored Data An examination into the registered speeds of american trotting horses, with remarks on their value as hereditary data

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T06:04:36.623327Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-16T06:04:35.651643Z digest=sha256:b802626fd09bb1e203b29bfe92a78fc89573ea9498f4c44df78f6d53e834a0f2

Observation 3e156e25-6cd5-423c-9884-b7e79f586771 · outbound

This paper cites Stochastic relaxation, gibbs distributions, and the bayesian restoration of images.

Learning High-dimensional Gaussians from Censored Data Stochastic relaxation, gibbs distributions, and the bayesian restoration of images

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T06:04:36.610195Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-16T06:04:35.655496Z digest=sha256:4a9919d0a8f0f327de1dbfaf274e3915bb748a481809c945fbec633aa4c56c8f

Observation e75eeb63-c555-44a1-bd3e-aaf1536c5d41 · outbound

This paper cites Learning mixtures of gaussians in high dimensions.

Learning High-dimensional Gaussians from Censored Data Learning mixtures of gaussians in high dimensions

Reference 49

Resolution
unresolved
no resolver link, observed 2026-08-16T06:04:35.660270Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T06:04:35.660270Z digest=sha256:769d17738b5cbef110984f45c89bcddc4d65b3f1be94b4dad9431d0d98c7faa9

Observation d9515d6e-4426-4d6e-ae9e-31b9fd219dae · outbound

This paper cites Sample selection bias as a specification error.

Learning High-dimensional Gaussians from Censored Data Sample selection bias as a specification error

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T06:04:36.589241Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-16T06:04:35.664043Z digest=sha256:ea31a4145148460448172624bd27346c6559c169208c79374683406d2654de22

Observation 2d7fa7f2-975a-42fb-a576-e0af5442fea8 · outbound

This paper cites What to do about missing values in time-series cross-section data.

Learning High-dimensional Gaussians from Censored Data What to do about missing values in time-series cross-section data

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T06:04:36.575734Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-16T06:04:35.667849Z digest=sha256:8163d1d0ba658a1d11a6d2edbc313d9d1bea8c07ce382fb3887e7126442631ce

Observation 174f7695-daee-4534-a1bc-bc578ac3e427 · outbound

This paper cites Robust and heavy-tailed mean estimation made simple, via regret minimization.

Learning High-dimensional Gaussians from Censored Data Robust and heavy-tailed mean estimation made simple, via regret minimization

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T06:04:36.562447Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-16T06:04:35.671629Z digest=sha256:acdca004f73eadf237d13c5de00e0dcccd19143bbd47ef77eb4093b775c7859f

Observation 5e570dda-fb46-4eb3-8545-8b99d23324e9 · outbound

This paper cites The method of simulated scores for the estimation of ldv models.

Learning High-dimensional Gaussians from Censored Data The method of simulated scores for the estimation of ldv models

Reference 53

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T06:04:36.549469Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-16T06:04:35.675409Z digest=sha256:292d8f3de1516e09b316eb63ae05628594ed55bd7ca5c81414a34e65a6259fb7

Observation 0528f7b5-5016-4730-bed3-d77fa26334aa · outbound

This paper cites Robust mean estimation on highly incomplete data with arbitrary outliers.

Learning High-dimensional Gaussians from Censored Data Robust mean estimation on highly incomplete data with arbitrary outliers

Reference 54

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T06:04:36.537241Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-16T06:04:35.678864Z digest=sha256:ef3cf2a4e4b11741de9e9d42aaec20b67e0f66b854f5fae81e5351003de6b6e9

Observation 5e04a8d5-3260-4a1e-aa7d-85e985a80d05 · outbound

This paper cites Estimation of averages in truncated samples.

Learning High-dimensional Gaussians from Censored Data Estimation of averages in truncated samples

Reference 55

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T06:04:36.524463Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-16T06:04:35.682690Z digest=sha256:9b5e0da28a492518ce4078ae23eb398036ad1cf0efa2ebcc2cc4b94fe77f74b1

Observation 81ab4188-c344-4fcd-9b90-d2e10061d600 · outbound

This paper cites Robust estimation of a location parameter.

Learning High-dimensional Gaussians from Censored Data Robust estimation of a location parameter

Reference 56

Resolution
unresolved
no resolver link, observed 2026-08-16T06:04:35.686961Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T06:04:35.686961Z digest=sha256:f1cf4cea8174dc2618755688661341a4753dc590386987489be5fbaa3bf1599e

Observation ffa22cb2-77c3-49ee-8224-a873da893f1a · outbound

This paper cites Social experimentation, truncated distributions, and efficient estimation.

Learning High-dimensional Gaussians from Censored Data Social experimentation, truncated distributions, and efficient estimation

Reference 57

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T06:04:36.502391Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-16T06:04:35.690995Z digest=sha256:3055adc5e47e3f977dd79b736c47021e00a3ac65846dca52a92deae2a744b8ec

Observation 589ab3cf-14d2-40a4-a771-713aca4bb2e0 · outbound

This paper cites Robust learning of mixtures of gaussians.

Learning High-dimensional Gaussians from Censored Data Robust learning of mixtures of gaussians

Reference 58

Resolution
unresolved
no resolver link, observed 2026-08-16T06:04:35.694675Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T06:04:35.694675Z digest=sha256:5121b237e06bae27e019cd8abc3be49b40fac23f52d9a08ff1bab05bdef1cc96

Observation b2b7ab68-b52d-46e3-9e31-beb733583206 · outbound

This paper cites What to Expect of Classifiers? Reasoning about Logistic Regression with Missing Features.

Learning High-dimensional Gaussians from Censored Data What to Expect of Classifiers? Reasoning about Logistic Regression with Missing Features

Reference 59

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unresolved
no resolver link, observed 2026-08-16T06:04:35.698648Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T06:04:35.698648Z digest=sha256:c6e764dc49aaac7285f2a5c80a0e57d3eefc323a3fbcd844efa1491f2abf10de

Observation 61b9b1b6-1e43-4bf1-a889-7ef6b26d5ee1 · outbound

This paper cites On the learnability of discrete distributions.

Learning High-dimensional Gaussians from Censored Data On the learnability of discrete distributions

Reference 60

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T06:04:36.480496Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-16T06:04:35.702683Z digest=sha256:d33a9fd347254048cbe69ddec76030980d09b8eee8e1a179e5179f6e27da6ce6

Observation b97f2f33-a657-4c9d-82e5-80c7975414ff · outbound

This paper cites Reduction of variance for gaussian densities via restriction to convex sets.

Learning High-dimensional Gaussians from Censored Data Reduction of variance for gaussian densities via restriction to convex sets

Reference 61

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T06:04:36.465844Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-16T06:04:35.706662Z digest=sha256:ef1bc35a296aeef4c898089f70fe3c259b380e9d984ebd22823d2886785dcbcd

Observation ce107e07-a2d9-4de4-a8be-29d48aff76fb · outbound

This paper cites Efficient truncated statistics with unknown truncation.

Learning High-dimensional Gaussians from Censored Data Efficient truncated statistics with unknown truncation

Reference 62

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T06:04:36.452319Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-16T06:04:35.710524Z digest=sha256:51bb62f5240dde70689c2a965205b6730129fec5d9b19a00913a51776588e4df

Observation a51a3988-f6ed-41b6-bf18-947c9fb8b349 · outbound

This paper cites The prevention and treatment of missing data in clinical trials.

Learning High-dimensional Gaussians from Censored Data The prevention and treatment of missing data in clinical trials

Reference 63

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T06:04:36.438710Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-16T06:04:35.714163Z digest=sha256:b97e3003cb2cbd482f50ebcf9c8321e3afe30a2cde5d039aad217a2a0797bcfd

Observation c1768cb1-56c0-4774-b553-9a9b94484c8f · outbound

This paper cites tail" functions; when the.

Learning High-dimensional Gaussians from Censored Data tail" functions; when the

Reference 64

Resolution
unresolved
no resolver link, observed 2026-08-16T06:04:35.718005Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T06:04:35.718005Z digest=sha256:7a911493b4fb2039a2198cbf906d30093f80f6558138e674e386b68e65f72100

Observation 9e0cfae1-9b7e-4da2-b253-60adce5f599b · outbound

This paper cites A fast spectral algorithm for mean estimation with sub-gaussian rates.

Learning High-dimensional Gaussians from Censored Data A fast spectral algorithm for mean estimation with sub-gaussian rates

Reference 65

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T06:04:36.418810Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-16T06:04:35.721794Z digest=sha256:6de53bd44e268ab8121de84af7429130a90dcc16dd513f21a322065ae92c6944

Observation a9ddd8d6-3634-4af6-9c54-b4e9aac8fa0a · outbound

This paper cites On robust mean estimation under coordinate-level corruption.

Learning High-dimensional Gaussians from Censored Data On robust mean estimation under coordinate-level corruption

Reference 66

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T06:04:36.406790Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-16T06:04:35.725475Z digest=sha256:612fe491a391a453b77d632a980dd788d09fd32d71d0dfbc434bcada8f312082

Observation 068525a3-3cf2-4f7e-88c6-275b8c2703d7 · outbound

This paper cites Statistical analysis with missing data , volume 793.

Learning High-dimensional Gaussians from Censored Data Statistical analysis with missing data , volume 793

Reference 67

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unresolved
no resolver link, observed 2026-08-16T06:04:35.728897Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T06:04:35.728897Z digest=sha256:f1bb5afd1083427328d86874089ab9076776460c38f69dfaf1e510c64d79064d

Observation 454be82d-9df9-4e4c-92b3-c41cb2b77261 · outbound

This paper cites Agnostic estimation of mean and covariance.

Learning High-dimensional Gaussians from Censored Data Agnostic estimation of mean and covariance

Reference 68

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T06:04:36.386881Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-16T06:04:35.732522Z digest=sha256:a125eca6364d1e4aa37bd77eeae8035bb3516c57bed18ec4b9604f72497fb860

Observation 38dae59b-37c9-4d55-b25e-47364bc1a784 · outbound

This paper cites Limited-dependent and qualitative variables in econometrics.

Learning High-dimensional Gaussians from Censored Data Limited-dependent and qualitative variables in econometrics

Reference 69

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T06:04:36.373601Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-16T06:04:35.736170Z digest=sha256:1bd83881679b017f7086e3d2a7637a09de9e78ef70bada19697218f89d362785

Observation db99cc0a-74b1-478e-8bdd-556e7ada57c5 · outbound

This paper cites Graphical models for inference with missing data.

Learning High-dimensional Gaussians from Censored Data Graphical models for inference with missing data

Reference 70

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T06:04:36.359136Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-16T06:04:35.740640Z digest=sha256:20bb42544d98c747cc6dba106384fa8f34b538956be1b3d101bcd9136fd7d9e2

Observation 8866fc01-e9c2-4f85-94fc-1fdede03875b · outbound

This paper cites Semiparametric inference for nonmonotone missing-not-at-random data: the no self-censoring model.

Learning High-dimensional Gaussians from Censored Data Semiparametric inference for nonmonotone missing-not-at-random data: the no self-censoring model

Reference 71

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T06:04:36.346218Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-16T06:04:35.744507Z digest=sha256:ab2c010b95760b28170a4a0e57038dc7b94a4a8de7c7afcb33ea55f66a761921

Observation 71ec2e69-447c-43d6-ba7b-156072b97d78 · outbound

This paper cites Full law identification in graphical models of missing data: Completeness results.

Learning High-dimensional Gaussians from Censored Data Full law identification in graphical models of missing data: Completeness results

Reference 72

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T06:04:36.334105Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-16T06:04:35.748302Z digest=sha256:15a0c64561c1d924ab94778d624e75b02039c21354f8021beebfde2f7cb8ce56

Observation 19f76d5f-1609-45a6-8ff9-9746023d12fc · outbound

This paper cites Parameter estimation for multivariate generalized gaussian distributions.

Learning High-dimensional Gaussians from Censored Data Parameter estimation for multivariate generalized gaussian distributions

Reference 73

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T06:04:36.320612Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-16T06:04:35.752850Z digest=sha256:29ce9173eba59432822f3c85f3ddbd890081dc973e6fa38aecea79df5595b58a

Observation f46edf41-8b65-44fa-b503-0cb0b99e61bb · outbound

This paper cites On the systematic fitting of curves to observations and measurements.

Learning High-dimensional Gaussians from Censored Data On the systematic fitting of curves to observations and measurements

Reference 74

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T06:04:36.305977Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-16T06:04:35.757031Z digest=sha256:47dce813f481ba375a67ae6001a6aef75e7e17d4a54829e5346b688e642c476f

Observation a83a364a-a257-456a-8d7f-dfa218445bb8 · outbound

This paper cites On the generalised probable error in multiple normal correlation.

Learning High-dimensional Gaussians from Censored Data On the generalised probable error in multiple normal correlation

Reference 75

Resolution
unresolved
no resolver link, observed 2026-08-16T06:04:35.761186Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T06:04:35.761186Z digest=sha256:1b173e0f739395319aebfa196f81248b5df035d9c765e2036c8a97d479a5e5fd

Observation dcd251df-aac0-4868-8612-f739bed4ece5 · outbound

This paper cites Learning from censored and dependent data: The case of linear dynamics.

Learning High-dimensional Gaussians from Censored Data Learning from censored and dependent data: The case of linear dynamics

Reference 76

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Observation 8e6b62b5-e453-417f-b4b3-0687e579ca41 · outbound

This paper cites Finite-Sample Guarantees for High-Dimensional DML.

Learning High-dimensional Gaussians from Censored Data Finite-Sample Guarantees for High-Dimensional DML

Reference 77

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Observation c82bf333-2797-4977-b012-3e33ae865dd4 · outbound

This paper cites HoloClean: Holistic Data Repairs with Probabilistic Inference.

Learning High-dimensional Gaussians from Censored Data HoloClean: Holistic Data Repairs with Probabilistic Inference

Reference 78

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Observation 43f778e6-55ff-44da-a0ba-620a13946dee · outbound

This paper cites Non-response models for the analysis of non-monotone ignorable missing data.

Learning High-dimensional Gaussians from Censored Data Non-response models for the analysis of non-monotone ignorable missing data

Reference 79

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Observation 968c0a62-37b7-4621-acd6-c4befdbbbbf4 · outbound

This paper cites Some thoughts on the distribution of earnings.

Learning High-dimensional Gaussians from Censored Data Some thoughts on the distribution of earnings

Reference 80

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Observation 2267d83a-7905-48b5-848a-c7469d4d7268 · outbound

This paper cites Semiparametric regression estimation in the presence of dependent censoring.

Learning High-dimensional Gaussians from Censored Data Semiparametric regression estimation in the presence of dependent censoring

Reference 81

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Observation d44a5ae9-6a7a-4416-8a1b-46138b2968bd · outbound

This paper cites Analysis of semi-parametric regression models with non-ignorable non-response.

Learning High-dimensional Gaussians from Censored Data Analysis of semi-parametric regression models with non-ignorable non-response

Reference 82

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Observation ee524c3d-25a2-46f7-867b-0c391b4f771f · outbound

This paper cites Semiparametric regression for repeated outcomes with nonignorable nonresponse.

Learning High-dimensional Gaussians from Censored Data Semiparametric regression for repeated outcomes with nonignorable nonresponse

Reference 83

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Observation c83218d4-3ded-41d2-a342-cee15bb555e0 · outbound

This paper cites Sensitivity analysis for selection bias and unmeasured confounding in missing data and causal inference models.

Learning High-dimensional Gaussians from Censored Data Sensitivity analysis for selection bias and unmeasured confounding in missing data and causal inference models

Reference 84

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Observation 318a4fcc-db09-4b58-9508-5360f415ddfe · outbound

This paper cites Robust learning with missing data.

Learning High-dimensional Gaussians from Censored Data Robust learning with missing data

Reference 85

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Observation 1a4e7071-6aae-4828-9930-7a6ba21a4cc3 · outbound

This paper cites Inference and missing data.

Learning High-dimensional Gaussians from Censored Data Inference and missing data

Reference 86

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Observation 92b713bb-bced-4acc-abde-e1a0bc25c05d · outbound

This paper cites Learning mixtures of arbitrary gaussians.

Learning High-dimensional Gaussians from Censored Data Learning mixtures of arbitrary gaussians

Reference 87

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Learning High-dimensional Gaussians from Censored Data Missing data as a causal and probabilistic problem

Reference 88

Resolution
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Observation b944794c-97b7-428d-9c60-c049fd66b0b4 · outbound

This paper cites Adjusting for nonignorable drop-out using semiparametric nonresponse models.

Learning High-dimensional Gaussians from Censored Data Adjusting for nonignorable drop-out using semiparametric nonresponse models

Reference 89

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Observation 6c544745-b3c7-4d92-b412-156c8a60211d · outbound

This paper cites Estimation of the mean of a multivariate normal distribution.

Learning High-dimensional Gaussians from Censored Data Estimation of the mean of a multivariate normal distribution

Reference 90

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Learning High-dimensional Gaussians from Censored Data Review of inverse probability weighting for dealing with missing data

Reference 91

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Observation 6309b8d9-6157-42db-a46c-b98f0eb08a7d · outbound

This paper cites Necessary and sufficient conditions for explicit solutions in the multivariate normal estimation problem for patterned means and covariances.

Learning High-dimensional Gaussians from Censored Data Necessary and sufficient conditions for explicit solutions in the multivariate normal estimation problem for patterned means and covariances

Reference 92

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Observation a9109a22-902f-467b-b1fe-94ac0a528a9f · outbound

This paper cites Statistical methods for robust inference in causal and missing data models.

Learning High-dimensional Gaussians from Censored Data Statistical methods for robust inference in causal and missing data models

Reference 93

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Observation c6f1dfab-49d9-48de-bdf8-a80c7f1caa1d · outbound

This paper cites Missing value estimation methods for dna microarrays.

Learning High-dimensional Gaussians from Censored Data Missing value estimation methods for dna microarrays

Reference 94

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Observation b61ae900-a6ce-42e1-af65-fae4ae8ea997 · outbound

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Learning High-dimensional Gaussians from Censored Data Estimation of relationships for limited dependent variables

Reference 95

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This paper cites Semiparametric theory and missing data.

Learning High-dimensional Gaussians from Censored Data Semiparametric theory and missing data

Reference 96

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Unavailable: canonical work link unavailable.

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Observation 0c955b27-629b-4061-83f2-4ec150932fb3 · outbound

This paper cites A survey of sampling from contaminated distributions.

Learning High-dimensional Gaussians from Censored Data A survey of sampling from contaminated distributions

Reference 97

Resolution
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Observation 31b818de-850e-478c-81a6-2b34b6335aa3 · outbound

This paper cites Discrete choice models for nonmonotone nonignorable missing data: Identification and inference.

Learning High-dimensional Gaussians from Censored Data Discrete choice models for nonmonotone nonignorable missing data: Identification and inference

Reference 98

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Observation c9728459-5f27-4113-8917-c1e6b23c38bb · outbound

This paper cites Flexible imputation of missing data.

Learning High-dimensional Gaussians from Censored Data Flexible imputation of missing data

Reference 99

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Observation 58853d62-6cff-4195-8a43-6c371cca159e · outbound

This paper cites Bond returns, liquidity, and missing data.

Learning High-dimensional Gaussians from Censored Data Bond returns, liquidity, and missing data

Reference 100

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Pith citing papers

Observation dedc6e19-bf35-4114-b5ba-b1ea24ca015c · inbound

High-Dimensional Statistics: Reflections on Progress and Open Problems cites this paper.

High-Dimensional Statistics: Reflections on Progress and Open Problems Learning High-dimensional Gaussians from Censored Data

Reference 7

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Observation 38c0758b-dc1e-4752-b1a7-4a64a2a4e86e · inbound

High-Dimensional Statistics: Reflections on Progress and Open Problems cites this paper.

High-Dimensional Statistics: Reflections on Progress and Open Problems Learning High-dimensional Gaussians from Censored Data

Reference 7

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