Paper Citation Record · LEDGER

Confidence Interval Construction and Conditional Variance Estimation with Dense ReLU Networks

As of 16 August 2026, this Paper Citation Record lists 66 of 66 outbound references and 2 inbound Pith citation observations for arXiv:2412.20355.

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

pith.paper-citation-record.v1
2412.20355 v2

Coverage vector

measured 66 of 66 reference resolution

Typed states for the displayed outbound observations.

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measured 2 of 2 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: pith, observed 2026-08-15T16:40:43.402848Z

Reference resolution

66 of 66 outbound references displayed

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External citation measurements

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Outbound references

Observation 62238638-ae6d-4397-8a45-7f8b11c09fca · outbound

This paper cites Robust variance estimation for the case-cohort design.

Confidence Interval Construction and Conditional Variance Estimation with Dense ReLU Networks Robust variance estimation for the case-cohort design

Reference 1

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This paper cites Nearly-tight vc-dimension and pseudodimension bounds for piecewise linear neural networks.

Confidence Interval Construction and Conditional Variance Estimation with Dense ReLU Networks Nearly-tight vc-dimension and pseudodimension bounds for piecewise linear neural networks

Reference 2

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Observation 25b6d6ac-f1f8-4ffa-b627-82b54b5612d8 · outbound

This paper cites On deep learning as a remedy for the curse of dimensionality in nonparametric regression.

Confidence Interval Construction and Conditional Variance Estimation with Dense ReLU Networks On deep learning as a remedy for the curse of dimensionality in nonparametric regression

Reference 3

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This paper cites Random forests.

Confidence Interval Construction and Conditional Variance Estimation with Dense ReLU Networks Random forests

Reference 4

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This paper cites Confidence intervals for nonparametric regression.

Confidence Interval Construction and Conditional Variance Estimation with Dense ReLU Networks Confidence intervals for nonparametric regression

Reference 5

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Observation 41f25661-15c5-4d8b-a251-7d0395fed17a · outbound

This paper cites Adaptive variance function estimation in heteroscedastic nonparametric regression.

Confidence Interval Construction and Conditional Variance Estimation with Dense ReLU Networks Adaptive variance function estimation in heteroscedastic nonparametric regression

Reference 6

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This paper cites Variance function estimation in multivariate nonparametric regression with fixed design.

Confidence Interval Construction and Conditional Variance Estimation with Dense ReLU Networks Variance function estimation in multivariate nonparametric regression with fixed design

Reference 7

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Observation a8afb48b-c319-4fbc-9184-27d8cb106439 · outbound

This paper cites Adaptive confidence bands for nonparametric regression functions.

Confidence Interval Construction and Conditional Variance Estimation with Dense ReLU Networks Adaptive confidence bands for nonparametric regression functions

Reference 8

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Observation 872d31c2-d535-4795-b890-daab9f666ab3 · outbound

This paper cites Simultaneous confidence bands for nonparametric regression with functional data.

Confidence Interval Construction and Conditional Variance Estimation with Dense ReLU Networks Simultaneous confidence bands for nonparametric regression with functional data

Reference 9

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Observation 9fd48259-7322-4e70-a04f-a19f0b4d45a3 · outbound

This paper cites Confidence bands in non-parametric errors-in-variables regression.

Confidence Interval Construction and Conditional Variance Estimation with Dense ReLU Networks Confidence bands in non-parametric errors-in-variables regression

Reference 10

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Observation ee1c97ff-2500-4ae6-8439-7fc803a8f9d1 · outbound

This paper cites Bootstrap methods: another look at the jackknife.

Confidence Interval Construction and Conditional Variance Estimation with Dense ReLU Networks Bootstrap methods: another look at the jackknife

Reference 11

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This paper cites An introduction to the bootstrap.

Confidence Interval Construction and Conditional Variance Estimation with Dense ReLU Networks An introduction to the bootstrap

Reference 12

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This paper cites Confidence bands in nonparametric regression.

Confidence Interval Construction and Conditional Variance Estimation with Dense ReLU Networks Confidence bands in nonparametric regression

Reference 13

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This paper cites Efficient estimation of conditional variance functions in stochastic regression.

Confidence Interval Construction and Conditional Variance Estimation with Dense ReLU Networks Efficient estimation of conditional variance functions in stochastic regression

Reference 14

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Observation 3d85e997-39d4-41a2-a08a-5cd364b84735 · outbound

This paper cites Deep neural networks for estimation and inference.

Confidence Interval Construction and Conditional Variance Estimation with Dense ReLU Networks Deep neural networks for estimation and inference

Reference 15

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Observation e7a13564-5ace-4b0a-842e-8e9793bdb8d8 · outbound

This paper cites Bootstrapping neural networks.

Confidence Interval Construction and Conditional Variance Estimation with Dense ReLU Networks Bootstrapping neural networks

Reference 16

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Observation 22ee4eab-cfea-4087-bed4-3f8cc5d0a606 · outbound

This paper cites Multivariate adaptive regression splines.

Confidence Interval Construction and Conditional Variance Estimation with Dense ReLU Networks Multivariate adaptive regression splines

Reference 17

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This paper cites Fast mars.

Confidence Interval Construction and Conditional Variance Estimation with Dense ReLU Networks Fast mars

Reference 18

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This paper cites Dropout as a bayesian approximation: Representing model uncertainty in deep learning.

Confidence Interval Construction and Conditional Variance Estimation with Dense ReLU Networks Dropout as a bayesian approximation: Representing model uncertainty in deep learning

Reference 19

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Confidence Interval Construction and Conditional Variance Estimation with Dense ReLU Networks Extremely randomized trees

Reference 20

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This paper cites Variance reduction techniques for estimating value-at-risk.

Confidence Interval Construction and Conditional Variance Estimation with Dense ReLU Networks Variance reduction techniques for estimating value-at-risk

Reference 21

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Confidence Interval Construction and Conditional Variance Estimation with Dense ReLU Networks Generative adversarial nets

Reference 22

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Confidence Interval Construction and Conditional Variance Estimation with Dense ReLU Networks Long short-term memory

Reference 23

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Confidence Interval Construction and Conditional Variance Estimation with Dense ReLU Networks o rfi, Michael K \

Reference 24

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Confidence Interval Construction and Conditional Variance Estimation with Dense ReLU Networks A distribution-free theory of nonparametric regression

Reference 25

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Confidence Interval Construction and Conditional Variance Estimation with Dense ReLU Networks On bootstrap confidence intervals in nonparametric regression

Reference 26

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This paper cites Variance function estimation in regression: the effect of estimating the mean.

Confidence Interval Construction and Conditional Variance Estimation with Dense ReLU Networks Variance function estimation in regression: the effect of estimating the mean

Reference 27

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This paper cites A simple bootstrap method for constructing nonparametric confidence bands for functions.

Confidence Interval Construction and Conditional Variance Estimation with Dense ReLU Networks A simple bootstrap method for constructing nonparametric confidence bands for functions

Reference 28

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This paper cites Nonasymptotic bounds on the l 2 error of neural network regression estimates.

Confidence Interval Construction and Conditional Variance Estimation with Dense ReLU Networks Nonasymptotic bounds on the l 2 error of neural network regression estimates

Reference 29

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This paper cites Bootstrapping in nonparametric regression: Local adaptive smoothing and confidence bands.

Confidence Interval Construction and Conditional Variance Estimation with Dense ReLU Networks Bootstrapping in nonparametric regression: Local adaptive smoothing and confidence bands

Reference 30

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This paper cites Robust conditional variance estimation and value-at-risk.

Confidence Interval Construction and Conditional Variance Estimation with Dense ReLU Networks Robust conditional variance estimation and value-at-risk

Reference 31

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Confidence Interval Construction and Conditional Variance Estimation with Dense ReLU Networks Adaptive regression estimation with multilayer feedforward neural networks

Reference 32

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This paper cites On the rate of convergence of fully connected very deep neural network regression estimates.

Confidence Interval Construction and Conditional Variance Estimation with Dense ReLU Networks On the rate of convergence of fully connected very deep neural network regression estimates

Reference 33

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This paper cites Variance function estimation in high-dimensions.

Confidence Interval Construction and Conditional Variance Estimation with Dense ReLU Networks Variance function estimation in high-dimensions

Reference 34

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Confidence Interval Construction and Conditional Variance Estimation with Dense ReLU Networks Imagenet classification with deep convolutional neural networks

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Confidence Interval Construction and Conditional Variance Estimation with Dense ReLU Networks Simple and scalable predictive uncertainty estimation using deep ensembles

Reference 36

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Confidence Interval Construction and Conditional Variance Estimation with Dense ReLU Networks Bootstrapping neural processes

Reference 37

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This paper cites Theoretical analysis of deep neural networks for temporally dependent observations.

Confidence Interval Construction and Conditional Variance Estimation with Dense ReLU Networks Theoretical analysis of deep neural networks for temporally dependent observations

Reference 38

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Confidence Interval Construction and Conditional Variance Estimation with Dense ReLU Networks Locally apadtive regression splines

Reference 39

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This paper cites The tight constant in the dvoretzky-kiefer-wolfowitz inequality.

Confidence Interval Construction and Conditional Variance Estimation with Dense ReLU Networks The tight constant in the dvoretzky-kiefer-wolfowitz inequality

Reference 40

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This paper cites Convergence rates for single hidden layer feedforward networks.

Confidence Interval Construction and Conditional Variance Estimation with Dense ReLU Networks Convergence rates for single hidden layer feedforward networks

Reference 41

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This paper cites earth: Multivariate Adaptive Regression Splines, 2024.

Confidence Interval Construction and Conditional Variance Estimation with Dense ReLU Networks earth: Multivariate Adaptive Regression Splines, 2024

Reference 42

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This paper cites Simultaneous bootstrap confidence bands in nonparametric regression.

Confidence Interval Construction and Conditional Variance Estimation with Dense ReLU Networks Simultaneous bootstrap confidence bands in nonparametric regression

Reference 43

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This paper cites Why aren’t bootstrapped neural networks better? In 34th Conference on Neural Information Processing Systems (NeurIPS 2020), Virtualonly Conference, 2020.

Confidence Interval Construction and Conditional Variance Estimation with Dense ReLU Networks Why aren’t bootstrapped neural networks better? In 34th Conference on Neural Information Processing Systems (NeurIPS 2020), Virtualonly Conference, 2020

Reference 44

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This paper cites Assessing and improving neural network predictions by the bootstrap algorithm.

Confidence Interval Construction and Conditional Variance Estimation with Dense ReLU Networks Assessing and improving neural network predictions by the bootstrap algorithm

Reference 45

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Confidence Interval Construction and Conditional Variance Estimation with Dense ReLU Networks Sparse spatial autoregressions

Reference 46

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This paper cites Variance estimation in graphs with the fused lasso.

Confidence Interval Construction and Conditional Variance Estimation with Dense ReLU Networks Variance estimation in graphs with the fused lasso

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:31:12.785115Z

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This paper cites Risk Bounds for Quantile Trend Filtering.

Confidence Interval Construction and Conditional Variance Estimation with Dense ReLU Networks Risk Bounds for Quantile Trend Filtering

Reference 48

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Observation a945a3ca-1b27-490b-8029-c4e07ff8b100 · outbound

This paper cites Quantile regression with relu networks: Estimators and minimax rates.

Confidence Interval Construction and Conditional Variance Estimation with Dense ReLU Networks Quantile regression with relu networks: Estimators and minimax rates

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:31:12.773503Z

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Observation 715645f0-fa71-4854-91b6-4a2d50a72681 · outbound

This paper cites Pedregosa, G.

Confidence Interval Construction and Conditional Variance Estimation with Dense ReLU Networks Pedregosa, G

Reference 50

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Confidence Interval Construction and Conditional Variance Estimation with Dense ReLU Networks Convex regression with interpretable sharp partitions

Reference 51

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Observation 3b51e51e-b688-4ff4-8d23-e1f2fe7f91c7 · outbound

This paper cites On confidence bands for multivariate nonparametric regression.

Confidence Interval Construction and Conditional Variance Estimation with Dense ReLU Networks On confidence bands for multivariate nonparametric regression

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:31:12.744898Z

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Observation d4111717-4d29-4d82-8ea6-c7d5019c2aea · outbound

This paper cites Nonlinear total variation based noise removal algorithms.

Confidence Interval Construction and Conditional Variance Estimation with Dense ReLU Networks Nonlinear total variation based noise removal algorithms

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:31:12.733665Z

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This paper cites Nonparametric regression using deep neural networks with relu activation function.

Confidence Interval Construction and Conditional Variance Estimation with Dense ReLU Networks Nonparametric regression using deep neural networks with relu activation function

Reference 54

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This paper cites Optimal estimation of variance in nonparametric regression with random design.

Confidence Interval Construction and Conditional Variance Estimation with Dense ReLU Networks Optimal estimation of variance in nonparametric regression with random design

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:31:12.716785Z

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Observation 91d4bd51-4573-4dcc-850e-24d1738434f1 · outbound

This paper cites Neural bootstrapper.

Confidence Interval Construction and Conditional Variance Estimation with Dense ReLU Networks Neural bootstrapper

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:31:12.707490Z

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This paper cites Deepface: Closing the gap to human-level performance in face verification.

Confidence Interval Construction and Conditional Variance Estimation with Dense ReLU Networks Deepface: Closing the gap to human-level performance in face verification

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:31:12.696549Z

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This paper cites Tibshirani.

Confidence Interval Construction and Conditional Variance Estimation with Dense ReLU Networks Tibshirani

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:31:12.686127Z

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Observation 8c7a52b4-3b2e-4488-ae6a-0d3b0e06b429 · outbound

This paper cites Weak convergence.

Confidence Interval Construction and Conditional Variance Estimation with Dense ReLU Networks Weak convergence

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:31:12.675472Z

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Observation bc6cee42-6410-4786-91a4-4150b137a95d · outbound

This paper cites Attention is all you need.

Confidence Interval Construction and Conditional Variance Estimation with Dense ReLU Networks Attention is all you need

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:31:12.665235Z

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Observation 2dc8c637-c2d3-4768-a02a-4fe3c2cd7e8f · outbound

This paper cites Methods to estimate the between-study variance and its uncertainty in meta-analysis.

Confidence Interval Construction and Conditional Variance Estimation with Dense ReLU Networks Methods to estimate the between-study variance and its uncertainty in meta-analysis

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:31:12.654731Z

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Observation bc38bd2c-a517-48bc-ab83-1e86a684e0dc · outbound

This paper cites High-dimensional statistics: A non-asymptotic viewpoint, volume 48.

Confidence Interval Construction and Conditional Variance Estimation with Dense ReLU Networks High-dimensional statistics: A non-asymptotic viewpoint, volume 48

Reference 62

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This paper cites Effect of mean on variance function estimation in nonparametric regression.

Confidence Interval Construction and Conditional Variance Estimation with Dense ReLU Networks Effect of mean on variance function estimation in nonparametric regression

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:31:12.635726Z

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Observation 4f39986f-65e0-4481-8381-c92db8f92bed · outbound

This paper cites Some asymptotic results for learning in single hidden-layer feedforward network models.

Confidence Interval Construction and Conditional Variance Estimation with Dense ReLU Networks Some asymptotic results for learning in single hidden-layer feedforward network models

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:31:12.624909Z

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Observation 53af6e6e-1546-4ff1-a354-2f30ed24a771 · outbound

This paper cites Bias-corrected confidence bands in nonparametric regression.

Confidence Interval Construction and Conditional Variance Estimation with Dense ReLU Networks Bias-corrected confidence bands in nonparametric regression

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:31:12.614755Z

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Observation f2b21479-435d-4d9a-9b9c-745ba8afc949 · outbound

This paper cites Dense ReLU Neural Networks for Temporal-spatial Model.

Confidence Interval Construction and Conditional Variance Estimation with Dense ReLU Networks Dense ReLU Neural Networks for Temporal-spatial Model

Reference 66

Resolution: verified exact; local_arxiv, observed 2026-08-10T23:31:12.572736Z

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Pith citing papers

Observation 9e778bb7-82f7-4398-a53a-299992bd2323 · inbound

Risk Bounds For Distributional Regression cites this paper.

Risk Bounds For Distributional Regression Confidence Interval Construction and Conditional Variance Estimation with Dense ReLU Networks

Reference 47

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Calibration Prediction Interval for Non-parametric Regression and Neural Networks cites this paper.

Calibration Prediction Interval for Non-parametric Regression and Neural Networks Confidence Interval Construction and Conditional Variance Estimation with Dense ReLU Networks

Reference 20

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