Paper Citation Record · LEDGER

Customer Lifetime Value Prediction with Uncertainty Estimation Using Monte Carlo Dropout

As of 13 August 2026, this Paper Citation Record lists 39 of 39 outbound references and 0 inbound Pith citation observations for arXiv:2411.15944.

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

pith.paper-citation-record.v1
2411.15944 v1

Coverage vector

measured 39 of 39 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T13:45:38.739038Z

measured 39 of 39 standing notices

One-hop event checks from named stored sources.

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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

39 of 39 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation c9254d0e-f183-4fae-bb83-00988171a2c2 · outbound

This paper cites Rfm and clv: Using iso-value curves for customer base analysis.

Customer Lifetime Value Prediction with Uncertainty Estimation Using Monte Carlo Dropout Rfm and clv: Using iso-value curves for customer base analysis

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:45:39.201301Z

Source-reported events for the cited work

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Observation f4785e3e-81b3-480d-bcec-cde2c41dedc0 · outbound

This paper cites counting your customers.

Customer Lifetime Value Prediction with Uncertainty Estimation Using Monte Carlo Dropout counting your customers

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:45:39.189154Z

Source-reported events for the cited work

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Observation f3c8fbb4-fc8c-47f6-abd7-313501a0496c · outbound

This paper cites Estimating customer lifetime value based on rfm analysis of customer purchase behavior: Case study.

Customer Lifetime Value Prediction with Uncertainty Estimation Using Monte Carlo Dropout Estimating customer lifetime value based on rfm analysis of customer purchase behavior: Case study

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:45:39.176153Z

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Observation a59d6ce3-b26a-4f33-b43d-0b49fdf011cd · outbound

This paper cites A Deep Probabilistic Model for Customer Lifetime Value Prediction.

Customer Lifetime Value Prediction with Uncertainty Estimation Using Monte Carlo Dropout A Deep Probabilistic Model for Customer Lifetime Value Prediction

Reference 4

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Observation 8b56d020-5cb7-47dd-a756-20c1fb443d81 · outbound

This paper cites percltv: A general system for personalized customer lifetime value prediction in online games.

Customer Lifetime Value Prediction with Uncertainty Estimation Using Monte Carlo Dropout percltv: A general system for personalized customer lifetime value prediction in online games

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:45:39.164500Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 9e02a0bb-c474-4069-a3c0-c21307d7a1d3 · outbound

This paper cites Customer lifetime value in video games using deep learning and parametric models.

Customer Lifetime Value Prediction with Uncertainty Estimation Using Monte Carlo Dropout Customer lifetime value in video games using deep learning and parametric models

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:45:39.152311Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 1a65c36c-c57c-4d33-841f-543d2b39cb23 · outbound

This paper cites Out of the box thinking: Improving customer lifetime value modelling via expert routing and game whale detection.

Customer Lifetime Value Prediction with Uncertainty Estimation Using Monte Carlo Dropout Out of the box thinking: Improving customer lifetime value modelling via expert routing and game whale detection

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:45:39.140571Z

Source-reported events for the cited work

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Observation ad83b24e-bfff-43d8-a43f-f9783a5c6784 · outbound

This paper cites Bayesian quicknat: Model uncertainty in deep whole-brain segmentation for structure-wise quality control.

Customer Lifetime Value Prediction with Uncertainty Estimation Using Monte Carlo Dropout Bayesian quicknat: Model uncertainty in deep whole-brain segmentation for structure-wise quality control

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:45:39.129268Z

Source-reported events for the cited work

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Observation 97786014-9074-4ca0-9680-5d942533fd4a · outbound

This paper cites Training Confidence-calibrated Classifiers for Detecting Out-of-Distribution Samples.

Customer Lifetime Value Prediction with Uncertainty Estimation Using Monte Carlo Dropout Training Confidence-calibrated Classifiers for Detecting Out-of-Distribution Samples

Reference 9

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Source-reported events for the cited work

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Observation c2369802-ed6a-4233-94c3-ee1727ff9ad4 · outbound

This paper cites On the Validity of Bayesian Neural Networks for Uncertainty Estimation.

Customer Lifetime Value Prediction with Uncertainty Estimation Using Monte Carlo Dropout On the Validity of Bayesian Neural Networks for Uncertainty Estimation

Reference 10

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Source-reported events for the cited work

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Observation 83fd1e4f-db4e-4f54-8450-6be70796b9ab · outbound

This paper cites Can you trust your model’s uncertainty? evaluating predictive uncertainty under dataset shift.

Customer Lifetime Value Prediction with Uncertainty Estimation Using Monte Carlo Dropout Can you trust your model’s uncertainty? evaluating predictive uncertainty under dataset shift

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-12T13:45:38.625969Z

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Observation 99a11c41-7b0e-461d-93ab-da23c8c33d67 · outbound

This paper cites Test-time data augmentation for estimation of heteroscedastic aleatoric uncertainty in deep neural networks.

Customer Lifetime Value Prediction with Uncertainty Estimation Using Monte Carlo Dropout Test-time data augmentation for estimation of heteroscedastic aleatoric uncertainty in deep neural networks

Reference 12

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Source-reported events for the cited work

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Observation 4f5fcecc-82b2-4ac7-95fa-c45f93c5f95e · outbound

This paper cites On calibration of modern neural networks.

Customer Lifetime Value Prediction with Uncertainty Estimation Using Monte Carlo Dropout On calibration of modern neural networks

Reference 13

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Source-reported events for the cited work

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Observation 59a68bb0-b027-4b64-9f62-dbc57c81bfdd · outbound

This paper cites Bayesian deep learning and a probabilistic perspective of generalization.

Customer Lifetime Value Prediction with Uncertainty Estimation Using Monte Carlo Dropout Bayesian deep learning and a probabilistic perspective of generalization

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:45:39.097450Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 794b526e-f1bd-43f0-8c0f-7665d1d9c413 · outbound

This paper cites Uncertainty in deep learning.

Customer Lifetime Value Prediction with Uncertainty Estimation Using Monte Carlo Dropout Uncertainty in deep learning

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:45:39.086240Z

Source-reported events for the cited work

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Observation bfa1aa25-6906-463d-9785-f5ca0bba81d1 · outbound

This paper cites Geometry and uncertainty in deep learning for computer vision.

Customer Lifetime Value Prediction with Uncertainty Estimation Using Monte Carlo Dropout Geometry and uncertainty in deep learning for computer vision

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:45:39.074507Z

Source-reported events for the cited work

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Observation a216e436-b71e-4ecc-b497-f25294997a35 · outbound

This paper cites Weight uncertainty in neural network.

Customer Lifetime Value Prediction with Uncertainty Estimation Using Monte Carlo Dropout Weight uncertainty in neural network

Reference 17

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Source-reported events for the cited work

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Observation bafad639-1616-4c2b-a212-dbd3315b5fd2 · outbound

This paper cites Dropconnect is effective in modeling uncertainty of bayesian deep networks.

Customer Lifetime Value Prediction with Uncertainty Estimation Using Monte Carlo Dropout Dropconnect is effective in modeling uncertainty of bayesian deep networks

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:45:39.055468Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 6f8aa134-3359-4881-874f-f5d560ef77ae · outbound

This paper cites Spatial Uncertainty Sampling for End-to-End Control.

Customer Lifetime Value Prediction with Uncertainty Estimation Using Monte Carlo Dropout Spatial Uncertainty Sampling for End-to-End Control

Reference 19

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Source-reported events for the cited work

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Observation 637600c3-b347-4c5c-9f2d-20be5ff5cb66 · outbound

This paper cites Bayesian Hypernetworks.

Customer Lifetime Value Prediction with Uncertainty Estimation Using Monte Carlo Dropout Bayesian Hypernetworks

Reference 20

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Source-reported events for the cited work

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Observation bcd21432-7a3f-4de7-a94e-d7b34fca293a · outbound

This paper cites Non-parametric calibration for classification.

Customer Lifetime Value Prediction with Uncertainty Estimation Using Monte Carlo Dropout Non-parametric calibration for classification

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:45:39.042909Z

Source-reported events for the cited work

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Observation ac53db05-74e1-464f-8f7a-c59b90936ccf · outbound

This paper cites Simple and scalable predictive uncertainty estimation using deep ensembles.

Customer Lifetime Value Prediction with Uncertainty Estimation Using Monte Carlo Dropout Simple and scalable predictive uncertainty estimation using deep ensembles

Reference 22

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Source-reported events for the cited work

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Observation 510ab783-1a1f-4a61-86fd-97835ac67190 · outbound

This paper cites Deep Sub-Ensembles for Fast Uncertainty Estimation in Image Classification.

Customer Lifetime Value Prediction with Uncertainty Estimation Using Monte Carlo Dropout Deep Sub-Ensembles for Fast Uncertainty Estimation in Image Classification

Reference 23

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Source-reported events for the cited work

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Observation a1a51353-8114-4f66-9613-b4e2bc4bc124 · outbound

This paper cites BatchEnsemble: An Alternative Approach to Efficient Ensemble and Lifelong Learning.

Customer Lifetime Value Prediction with Uncertainty Estimation Using Monte Carlo Dropout BatchEnsemble: An Alternative Approach to Efficient Ensemble and Lifelong Learning

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-12T13:45:38.676561Z

Source-reported events for the cited work

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Observation d4e461ec-a953-42d5-8f42-a415a15011d4 · outbound

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

Customer Lifetime Value Prediction with Uncertainty Estimation Using Monte Carlo Dropout Dropout as a bayesian approximation: Representing model uncertainty in deep learning

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-12T13:45:38.680672Z

Source-reported events for the cited work

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Observation 183bfdb2-f12f-4c5c-8b98-1e0a5fdde9e0 · outbound

This paper cites Harnessing model uncertainty for detecting adversarial examples.

Customer Lifetime Value Prediction with Uncertainty Estimation Using Monte Carlo Dropout Harnessing model uncertainty for detecting adversarial examples

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:45:39.014077Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 706fc542-42b6-46a5-8762-9d679cc53c6f · outbound

This paper cites Understanding Measures of Uncertainty for Adversarial Example Detection.

Customer Lifetime Value Prediction with Uncertainty Estimation Using Monte Carlo Dropout Understanding Measures of Uncertainty for Adversarial Example Detection

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-12T13:45:38.688306Z

Source-reported events for the cited work

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Observation 57cf0ea0-b911-491a-a3d3-6d9acefd94d6 · outbound

This paper cites Adversarial Examples - A Complete Characterisation of the Phenomenon.

Customer Lifetime Value Prediction with Uncertainty Estimation Using Monte Carlo Dropout Adversarial Examples - A Complete Characterisation of the Phenomenon

Reference 28

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Source-reported events for the cited work

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Observation 4db391a6-0d3f-4eb0-9201-d04f8a486dd5 · outbound

This paper cites Predictive uncertainty estimation via prior networks.Advances in neural information processing systems, 31, 2018.

Customer Lifetime Value Prediction with Uncertainty Estimation Using Monte Carlo Dropout Predictive uncertainty estimation via prior networks.Advances in neural information processing systems, 31, 2018

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-12T13:45:38.697178Z

Source-reported events for the cited work

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Observation 0e01a330-c800-47f6-9fc0-6bb12501afcb · outbound

This paper cites Information robust dirichlet networks for predictive uncertainty estimation, April 8 2021.

Customer Lifetime Value Prediction with Uncertainty Estimation Using Monte Carlo Dropout Information robust dirichlet networks for predictive uncertainty estimation, April 8 2021

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:45:38.995768Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation d51184f5-aefd-4392-b6d7-3684c523ad5c · outbound

This paper cites Evidential deep learning to quantify classification uncertainty.

Customer Lifetime Value Prediction with Uncertainty Estimation Using Monte Carlo Dropout Evidential deep learning to quantify classification uncertainty

Reference 31

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Source-reported events for the cited work

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Observation 01107fbd-c5ac-4c0d-aaee-53a1f1a635ae · outbound

This paper cites Ensemble Distribution Distillation.

Customer Lifetime Value Prediction with Uncertainty Estimation Using Monte Carlo Dropout Ensemble Distribution Distillation

Reference 32

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Source-reported events for the cited work

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Observation e26e5a81-325d-460d-b4d9-2642f0f33f54 · outbound

This paper cites Direct uncertainty prediction for medical second opinions.

Customer Lifetime Value Prediction with Uncertainty Estimation Using Monte Carlo Dropout Direct uncertainty prediction for medical second opinions

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:45:38.975089Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 8ec8954d-3606-4c8c-9c92-22c4a7e490c5 · outbound

This paper cites Dcn v2: Improved deep & cross network and practical lessons for web-scale learning to rank systems.

Customer Lifetime Value Prediction with Uncertainty Estimation Using Monte Carlo Dropout Dcn v2: Improved deep & cross network and practical lessons for web-scale learning to rank systems

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:45:38.962153Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation e5639200-8222-461d-98ba-5cf531aa6556 · outbound

This paper cites Free-to-play: About addicted whales, at risk dolphins and healthy minnows.

Customer Lifetime Value Prediction with Uncertainty Estimation Using Monte Carlo Dropout Free-to-play: About addicted whales, at risk dolphins and healthy minnows

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:45:38.950591Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 88a87330-c7cc-4498-9ffc-337f87f59654 · outbound

This paper cites Whales, dolphins, or minnows? towards the player clustering in free online games based on purchasing behavior via data mining technique.

Customer Lifetime Value Prediction with Uncertainty Estimation Using Monte Carlo Dropout Whales, dolphins, or minnows? towards the player clustering in free online games based on purchasing behavior via data mining technique

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:45:38.938107Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation ba09f762-92c3-413f-b4d9-68de458ea7ab · outbound

This paper cites From minnows to whales: An empirical study of purchase behavior in freemium social games.

Customer Lifetime Value Prediction with Uncertainty Estimation Using Monte Carlo Dropout From minnows to whales: An empirical study of purchase behavior in freemium social games

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:45:38.924111Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 6f6cf084-cebb-479f-849d-545f94b10217 · outbound

This paper cites Ensemble deep learning: A review.

Customer Lifetime Value Prediction with Uncertainty Estimation Using Monte Carlo Dropout Ensemble deep learning: A review

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:45:38.911231Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 547c63c4-d2f5-4162-b7d4-877fc6051214 · outbound

This paper cites Deep Ensembles: A Loss Landscape Perspective.

Customer Lifetime Value Prediction with Uncertainty Estimation Using Monte Carlo Dropout Deep Ensembles: A Loss Landscape Perspective

Reference 39

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Pith citing papers

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