Paper Citation Record · LEDGER

Prediction Models That Learn to Avoid Missing Values

As of 17 August 2026, this Paper Citation Record lists 46 of 46 outbound references and 0 inbound Pith citation observations for arXiv:2505.03393.

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

pith.paper-citation-record.v1
2505.03393 v1

Coverage vector

measured 46 of 46 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T23:59:58.247827Z

measured 46 of 46 standing notices

One-hop event checks from named stored sources.

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measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

46 of 46 outbound references displayed

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External citation measurements

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Outbound references

Observation a5dbec24-38ce-4aaa-95e7-a95f35ad56ca · outbound

This paper cites write newline.

Prediction Models That Learn to Avoid Missing Values write newline

Reference 1

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This paper cites and Rosenthal, J.

Prediction Models That Learn to Avoid Missing Values and Rosenthal, J

Reference 2

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Observation 66c666b2-ee7a-40ea-86a0-8317feea83f7 · outbound

This paper cites and Guestrin, C.

Prediction Models That Learn to Avoid Missing Values and Guestrin, C

Reference 3

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This paper cites Why do Random Forests Work? Understanding Tree Ensembles as Self-Regularizing Adaptive Smoothers.

Prediction Models That Learn to Avoid Missing Values Why do Random Forests Work? Understanding Tree Ensembles as Self-Regularizing Adaptive Smoothers

Reference 4

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This paper cites and Bj rner, N.

Prediction Models That Learn to Avoid Missing Values and Bj rner, N

Reference 5

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Observation 823afaf6-4f6b-4be5-a991-e24d0fc3d44f · outbound

This paper cites Learning sparse classifiers: Continuous and mixed integer optimization perspectives.

Prediction Models That Learn to Avoid Missing Values Learning sparse classifiers: Continuous and mixed integer optimization perspectives

Reference 6

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Observation b513da47-1b5e-4a63-b18c-305a190c24b1 · outbound

This paper cites Explainable machine learning challenge, 2018.

Prediction Models That Learn to Avoid Missing Values Explainable machine learning challenge, 2018

Reference 7

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This paper cites and Blume, J.

Prediction Models That Learn to Avoid Missing Values and Blume, J

Reference 8

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Observation 8863f147-4b6b-4e14-8167-b4eb8615d1bd · outbound

This paper cites Benchmarking distribution shift in tabular data with tableshift.

Prediction Models That Learn to Avoid Missing Values Benchmarking distribution shift in tabular data with tableshift

Reference 9

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Observation a2e6df61-8037-4875-a3a2-b0551ebbb9ba · outbound

This paper cites Gurobi Optimizer Reference Manual, 2024.

Prediction Models That Learn to Avoid Missing Values Gurobi Optimizer Reference Manual, 2024

Reference 10

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Observation 162c4432-0c15-481a-9edf-266f512a0499 · outbound

This paper cites The Elements of Statistical Learning: Data Mining, Inference, and Prediction.

Prediction Models That Learn to Avoid Missing Values The Elements of Statistical Learning: Data Mining, Inference, and Prediction

Reference 11

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Observation a0b17dcd-b259-439a-8765-6043e28c5bc0 · outbound

This paper cites User's Manual for CPLEX , 2010.

Prediction Models That Learn to Avoid Missing Values User's Manual for CPLEX , 2010

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:59:58.820926Z

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Observation e2d96552-3e30-42b2-97c7-33a3f63bac45 · outbound

This paper cites Imputation strategies under clinical presence: Impact on algorithmic fairness.

Prediction Models That Learn to Avoid Missing Values Imputation strategies under clinical presence: Impact on algorithmic fairness

Reference 13

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This paper cites L., Paulose-Ram, R., Ogden, C.

Prediction Models That Learn to Avoid Missing Values L., Paulose-Ram, R., Ogden, C

Reference 14

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This paper cites M., Prost, N., Varoquaux, G., and Scornet, E.

Prediction Models That Learn to Avoid Missing Values M., Prost, N., Varoquaux, G., and Scornet, E

Reference 15

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This paper cites and Bleich, J.

Prediction Models That Learn to Avoid Missing Values and Bleich, J

Reference 16

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Observation bc32e4f6-cba7-4e5d-90c5-b34fdb6520dc · outbound

This paper cites Auto-Encoding Variational Bayes.

Prediction Models That Learn to Avoid Missing Values Auto-Encoding Variational Bayes

Reference 17

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Observation 0c3be179-2719-4cd8-a023-614e06d4e075 · outbound

This paper cites Miracle: Causally-aware imputation via learning missing data mechanisms.

Prediction Models That Learn to Avoid Missing Values Miracle: Causally-aware imputation via learning missing data mechanisms

Reference 18

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Observation cdb5afcd-ae19-4670-becd-280a3aaac283 · outbound

This paper cites NeuMiss networks: Differentiable programming for supervised learning with missing values.

Prediction Models That Learn to Avoid Missing Values NeuMiss networks: Differentiable programming for supervised learning with missing values

Reference 19

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Observation 670c914a-7cb8-4c1f-85d8-ff618f5c6283 · outbound

This paper cites What’s a good imputation to predict with missing values? In Advances in Neural Information Processing Systems 34, pp.\ 11530--11540, 2021.

Prediction Models That Learn to Avoid Missing Values What’s a good imputation to predict with missing values? In Advances in Neural Information Processing Systems 34, pp.\ 11530--11540, 2021

Reference 20

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Observation ab883472-aa0d-4c8b-97c1-16e6d3adcfb6 · outbound

This paper cites Fast sparse classification for generalized linear and additive models.

Prediction Models That Learn to Avoid Missing Values Fast sparse classification for generalized linear and additive models

Reference 21

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This paper cites and Chen, G.

Prediction Models That Learn to Avoid Missing Values and Chen, G

Reference 22

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Observation ad04ff20-7a7d-4b1b-9533-38aac3d7b516 · outbound

This paper cites R-miss-tastic: A unified platform for missing values methods and workflows.

Prediction Models That Learn to Avoid Missing Values R-miss-tastic: A unified platform for missing values methods and workflows

Reference 23

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Observation 473ffdb2-22b3-4448-9d40-893c5a59aac6 · outbound

This paper cites Interpretable generalized additive models for datasets with missing values.

Prediction Models That Learn to Avoid Missing Values Interpretable generalized additive models for datasets with missing values

Reference 24

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Observation 85ce7e83-bf04-4a04-8399-701423b1240d · outbound

This paper cites Identifying group a streptococcal pharyngitis in children through clinical variables using machine learning.

Prediction Models That Learn to Avoid Missing Values Identifying group a streptococcal pharyngitis in children through clinical variables using machine learning

Reference 25

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This paper cites PyTorch : An imperative style, high-performance deep learning library.

Prediction Models That Learn to Avoid Missing Values PyTorch : An imperative style, high-performance deep learning library

Reference 26

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This paper cites Probabilistic reasoning in intelligent systems: Networks of plausible inference.

Prediction Models That Learn to Avoid Missing Values Probabilistic reasoning in intelligent systems: Networks of plausible inference

Reference 27

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This paper cites Scikit-learn: Machine learning in Python.

Prediction Models That Learn to Avoid Missing Values Scikit-learn: Machine learning in Python

Reference 28

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Prediction Models That Learn to Avoid Missing Values Unresolved cited work

Reference 29

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Reference 30

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Prediction Models That Learn to Avoid Missing Values T., Xu, G., Bandlamudi, C., Ross, D

Reference 31

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Prediction Models That Learn to Avoid Missing Values Unresolved cited work

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This paper cites Interpretable machine learning: Fundamental principles and 10 grand challenges.

Prediction Models That Learn to Avoid Missing Values Interpretable machine learning: Fundamental principles and 10 grand challenges

Reference 33

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This paper cites On the existence of simpler machine learning models.

Prediction Models That Learn to Avoid Missing Values On the existence of simpler machine learning models

Reference 34

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This paper cites V., Sala, E., Li \'o , P., et al.

Prediction Models That Learn to Avoid Missing Values V., Sala, E., Li \'o , P., et al

Reference 35

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This paper cites and Johansson, F.

Prediction Models That Learn to Avoid Missing Values and Johansson, F

Reference 36

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Prediction Models That Learn to Avoid Missing Values Unresolved cited work

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Prediction Models That Learn to Avoid Missing Values Regression shrinkage and selection via the Lasso

Reference 38

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This paper cites J., Nouri, D., Bossan, B., and skorch Developers.

Prediction Models That Learn to Avoid Missing Values J., Nouri, D., Bossan, B., and skorch Developers

Reference 39

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This paper cites E., Jones, M., and Hand, D.

Prediction Models That Learn to Avoid Missing Values E., Jones, M., and Hand, D

Reference 40

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This paper cites Flexible multivariate imputation by MICE.

Prediction Models That Learn to Avoid Missing Values Flexible multivariate imputation by MICE

Reference 41

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Prediction Models That Learn to Avoid Missing Values M., Halpin-Gregorio, R., and Udell, M

Reference 42

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Prediction Models That Learn to Avoid Missing Values H., and Moons, K

Reference 43

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Prediction Models That Learn to Avoid Missing Values and Zhang, Y

Reference 44

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This paper cites W., Aisen, P.

Prediction Models That Learn to Avoid Missing Values W., Aisen, P

Reference 45

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Observation 0f128176-7740-4623-b342-a79297180c36 · outbound

This paper cites Global Health Estimates : Life expectancy and healthy life expectancy, 2021.

Prediction Models That Learn to Avoid Missing Values Global Health Estimates : Life expectancy and healthy life expectancy, 2021

Reference 46

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Pith citing papers

No inbound Pith citation observations are available.