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Paper Citation Record · LEDGER

Comparative Analysis of Global and Local Probabilistic Time Series Forecasting for Contiguous Spatial Demand Regions

As of 10 August 2026, this Paper Citation Record lists 47 of 47 outbound references and 0 inbound Pith citation observations for arXiv:2509.08214.

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

pith.paper-citation-record.v1
2509.08214 v1

Coverage vector

measured 47 of 47 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-04T21:06:24.656279Z

measured 47 of 47 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

47 of 47 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 2b6abbbb-d076-474b-b685-c8088c92a250 · outbound

This paper cites an unresolved cited work.

Comparative Analysis of Global and Local Probabilistic Time Series Forecasting for Contiguous Spatial Demand Regions Unresolved cited work

Reference 1

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Observation 437bacfe-6f78-4d43-9df5-862386832621 · outbound

This paper cites Time-series clustering – A decade review.Information Systems, 53:16–38, October 2015.

Comparative Analysis of Global and Local Probabilistic Time Series Forecasting for Contiguous Spatial Demand Regions Time-series clustering – A decade review.Information Systems, 53:16–38, October 2015

Reference 2

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation a244925a-af01-424e-bd99-252f7b8f472b · outbound

This paper cites an unresolved cited work.

Comparative Analysis of Global and Local Probabilistic Time Series Forecasting for Contiguous Spatial Demand Regions Unresolved cited work

Reference 3

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Observation 3ce52745-112d-4390-9dea-634726d6a334 · outbound

This paper cites Assimakopoulos and K.

Comparative Analysis of Global and Local Probabilistic Time Series Forecasting for Contiguous Spatial Demand Regions Assimakopoulos and K

Reference 4

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Source-reported events for the cited work

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Observation a82c2bb8-74c5-470a-a2e0-a4c3a7a1da9f · outbound

This paper cites an unresolved cited work.

Comparative Analysis of Global and Local Probabilistic Time Series Forecasting for Contiguous Spatial Demand Regions Unresolved cited work

Reference 5

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 064fe225-a31e-45a3-95c7-f46a2bc62089 · outbound

This paper cites an unresolved cited work.

Comparative Analysis of Global and Local Probabilistic Time Series Forecasting for Contiguous Spatial Demand Regions Unresolved cited work

Reference 6

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 0d6a379f-d5fc-452e-a3ae-3f7a5e88c16c · outbound

This paper cites Carney, P.

Comparative Analysis of Global and Local Probabilistic Time Series Forecasting for Contiguous Spatial Demand Regions Carney, P

Reference 7

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation f1451fd3-e4cd-47bd-87c6-f8e6145776ad · outbound

This paper cites Model-based clustering with Hidden Markov Model regression for time series with regime changes.

Comparative Analysis of Global and Local Probabilistic Time Series Forecasting for Contiguous Spatial Demand Regions Model-based clustering with Hidden Markov Model regression for time series with regime changes

Reference 8

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation a896fb13-1dbc-4c0a-9b35-208aa2dca17a · outbound

This paper cites Calculating Interval Forecasts.Journal of Business & Economic Statistics, 11(2):121–135, April 1993.

Comparative Analysis of Global and Local Probabilistic Time Series Forecasting for Contiguous Spatial Demand Regions Calculating Interval Forecasts.Journal of Business & Economic Statistics, 11(2):121–135, April 1993

Reference 9

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 0026bfcb-121e-4bef-ab21-2efdae4572ce · outbound

This paper cites XGBoost: A Scalable Tree Boosting System.

Comparative Analysis of Global and Local Probabilistic Time Series Forecasting for Contiguous Spatial Demand Regions XGBoost: A Scalable Tree Boosting System

Reference 10

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 72808b13-06ea-4988-8ba4-c5488b4bf742 · outbound

This paper cites Research on the Urban Bike-sharing Usage based on ARIMA Model.Transactions on Computer Science and Intelligent Systems Research, 5:166–172, August 2024.

Comparative Analysis of Global and Local Probabilistic Time Series Forecasting for Contiguous Spatial Demand Regions Research on the Urban Bike-sharing Usage based on ARIMA Model.Transactions on Computer Science and Intelligent Systems Research, 5:166–172, August 2024

Reference 11

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation dfbc97ee-6f0a-4a26-bdb5-4960785dbb1e · outbound

This paper cites ACS 5 Year Data by Ward, February 2025.

Comparative Analysis of Global and Local Probabilistic Time Series Forecasting for Contiguous Spatial Demand Regions ACS 5 Year Data by Ward, February 2025

Reference 12

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation bf52c097-8568-4219-9aa0-eeb395d3d520 · outbound

This paper cites Chicago Transit Authority (CTA) Open data, 2022.

Comparative Analysis of Global and Local Probabilistic Time Series Forecasting for Contiguous Spatial Demand Regions Chicago Transit Authority (CTA) Open data, 2022

Reference 13

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation fd2375a5-3bc3-4091-b23c-600fb6a09ea5 · outbound

This paper cites Kempa-Liehr.

Comparative Analysis of Global and Local Probabilistic Time Series Forecasting for Contiguous Spatial Demand Regions Kempa-Liehr

Reference 14

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 93a2db77-5730-4fd4-8956-82790700e328 · outbound

This paper cites Divvy Data, June 2025.

Comparative Analysis of Global and Local Probabilistic Time Series Forecasting for Contiguous Spatial Demand Regions Divvy Data, June 2025

Reference 15

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation fe00fe9a-bfd1-4754-9196-1de5d2090950 · outbound

This paper cites NGBoost: Natural Gradient Boosting for Probabilistic Prediction.

Comparative Analysis of Global and Local Probabilistic Time Series Forecasting for Contiguous Spatial Demand Regions NGBoost: Natural Gradient Boosting for Probabilistic Prediction

Reference 16

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Source-reported events for the cited work

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Observation 9a2bb05e-c7ce-4917-8f47-abc84f916576 · outbound

This paper cites an unresolved cited work.

Comparative Analysis of Global and Local Probabilistic Time Series Forecasting for Contiguous Spatial Demand Regions Unresolved cited work

Reference 17

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation bb432bc0-7b07-40fc-8c06-eb1abb2108be · outbound

This paper cites Gao, S.R.

Comparative Analysis of Global and Local Probabilistic Time Series Forecasting for Contiguous Spatial Demand Regions Gao, S.R

Reference 18

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 95392d1a-e4d3-4065-b222-dd0194877ad0 · outbound

This paper cites Hashem Pesaran and Takashi Yamagata.

Comparative Analysis of Global and Local Probabilistic Time Series Forecasting for Contiguous Spatial Demand Regions Hashem Pesaran and Takashi Yamagata

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T21:06:26.180153Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 004aca77-c5b5-432c-bb26-735bd1abc30a · outbound

This paper cites Global models for time series forecasting: A Simulation study.Pattern Recognition, 124:108441, April 2022.

Comparative Analysis of Global and Local Probabilistic Time Series Forecasting for Contiguous Spatial Demand Regions Global models for time series forecasting: A Simulation study.Pattern Recognition, 124:108441, April 2022

Reference 20

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 55e07a28-49ff-4e3f-81fd-2534bffdd6a5 · outbound

This paper cites Model selection for count timeseries with applications in forecasting number of trips in bike-sharing systems and its volatility.

Comparative Analysis of Global and Local Probabilistic Time Series Forecasting for Contiguous Spatial Demand Regions Model selection for count timeseries with applications in forecasting number of trips in bike-sharing systems and its volatility

Reference 21

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 311e9c67-0838-4ab8-907a-fae35a737318 · outbound

This paper cites A state space framework for automatic forecasting using exponential smoothing methods.International Journal of Forecasting, 18(3):439–454, July 2002.

Comparative Analysis of Global and Local Probabilistic Time Series Forecasting for Contiguous Spatial Demand Regions A state space framework for automatic forecasting using exponential smoothing methods.International Journal of Forecasting, 18(3):439–454, July 2002

Reference 22

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 7285f201-1ee9-422c-8bec-a7c2e830ac5f · outbound

This paper cites Johnson, Miles Q.

Comparative Analysis of Global and Local Probabilistic Time Series Forecasting for Contiguous Spatial Demand Regions Johnson, Miles Q

Reference 23

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation e22f90db-7764-4f31-806e-6d9033be685b · outbound

This paper cites LightGBM: A Highly Efficient Gradient Boosting Decision Tree.

Comparative Analysis of Global and Local Probabilistic Time Series Forecasting for Contiguous Spatial Demand Regions LightGBM: A Highly Efficient Gradient Boosting Decision Tree

Reference 24

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raw_fallback, observed 2026-08-04T21:06:26.135089Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-04T21:06:23.772499Z digest=sha256:77f9e03859a20e192f231ae3eef32fb137e53da5da328bd0785e45f60930d998

Observation ce1dafc8-d02c-4f5a-82ba-3c708f413264 · outbound

This paper cites Regression Quantiles.Econometrica, 46(1):33, January 1978.

Comparative Analysis of Global and Local Probabilistic Time Series Forecasting for Contiguous Spatial Demand Regions Regression Quantiles.Econometrica, 46(1):33, January 1978

Reference 25

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verified fuzzy
raw_fallback, observed 2026-08-04T21:06:26.123681Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation de7cb1ec-c77f-49ee-b300-ce594c0dd6a9 · outbound

This paper cites Predict, Refine, Synthesize: Self-Guiding Diffusion Models for Probabilistic Time Series Forecasting, 2023.

Comparative Analysis of Global and Local Probabilistic Time Series Forecasting for Contiguous Spatial Demand Regions Predict, Refine, Synthesize: Self-Guiding Diffusion Models for Probabilistic Time Series Forecasting, 2023

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T21:06:26.112506Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation bc93ece1-0e08-4261-a037-85087a38f777 · outbound

This paper cites Tsoukalas.

Comparative Analysis of Global and Local Probabilistic Time Series Forecasting for Contiguous Spatial Demand Regions Tsoukalas

Reference 27

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verified fuzzy
raw_fallback, observed 2026-08-04T21:06:26.101606Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 802d7d4c-7058-4e02-94c1-8f222784501c · outbound

This paper cites an unresolved cited work.

Comparative Analysis of Global and Local Probabilistic Time Series Forecasting for Contiguous Spatial Demand Regions Unresolved cited work

Reference 28

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unresolved
raw_fallback, observed 2026-08-04T21:06:26.090857Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation d20a038a-fe5f-444a-aa2d-4e5076746908 · outbound

This paper cites Principal components analysis (PCA).

Comparative Analysis of Global and Local Probabilistic Time Series Forecasting for Contiguous Spatial Demand Regions Principal components analysis (PCA)

Reference 29

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T21:06:26.080365Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-04T21:06:24.029340Z digest=sha256:3e4b578b8a384520d77a9209583f7a1b166a72f431688ca2803fa9be5d672281

Observation 6053bbfb-5853-4c32-bae4-594f17eabb01 · outbound

This paper cites Quantile Regression Forests.Journal of Machine Learning Research, 7(35):983–999, 2006.

Comparative Analysis of Global and Local Probabilistic Time Series Forecasting for Contiguous Spatial Demand Regions Quantile Regression Forests.Journal of Machine Learning Research, 7(35):983–999, 2006

Reference 30

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verified fuzzy
raw_fallback, observed 2026-08-04T21:06:26.070259Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 782a9e7c-d0bd-4445-91be-ee251efb74ac · outbound

This paper cites an unresolved cited work.

Comparative Analysis of Global and Local Probabilistic Time Series Forecasting for Contiguous Spatial Demand Regions Unresolved cited work

Reference 31

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unresolved
raw_fallback, observed 2026-08-04T21:06:26.058516Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-04T21:06:24.084154Z digest=sha256:f1f79b1423910b0bd7e7baa8ef2cdf2619696554ba2b8c0f9b98727f92035d57

Observation a4eaab5d-602e-45f4-9fb1-ddd427588056 · outbound

This paper cites Nix and A.S.

Comparative Analysis of Global and Local Probabilistic Time Series Forecasting for Contiguous Spatial Demand Regions Nix and A.S

Reference 32

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verified fuzzy
raw_fallback, observed 2026-08-04T21:06:26.047313Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-04T21:06:24.132340Z digest=sha256:7c22d7c56b8c19bf78d9549951eb2be9519500f93007fc3323f34338e8d4b6e2

Observation e25c64f5-77c1-42b3-b154-2e72e35222dd · outbound

This paper cites Note on Regression and Inheritance in the Case of Two Parents.Proceedings of the Royal Society of London, 58:240–242, 1895.

Comparative Analysis of Global and Local Probabilistic Time Series Forecasting for Contiguous Spatial Demand Regions Note on Regression and Inheritance in the Case of Two Parents.Proceedings of the Royal Society of London, 58:240–242, 1895

Reference 33

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raw_fallback, observed 2026-08-04T21:06:26.035836Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-04T21:06:24.179855Z digest=sha256:05313800b7583ecb928eb5cf8d73727af5073ef3c22646f8aa4b62f27270652b

Observation 0b823218-9d01-449c-a291-cd67c96bdede · outbound

This paper cites Managing Supply and Demand Balance Through Machine Learning, June 2021.

Comparative Analysis of Global and Local Probabilistic Time Series Forecasting for Contiguous Spatial Demand Regions Managing Supply and Demand Balance Through Machine Learning, June 2021

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T21:06:26.024013Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-04T21:06:24.207330Z digest=sha256:5fa8635f498771557b7c740bb73bc24ee45fe33b717cd4d458d6e7e5ef609127

Observation e262a63b-1ae3-4f95-8a28-105194111ace · outbound

This paper cites Finding a "Kneedle" in a Haystack: Detecting Knee Points in System Behavior.

Comparative Analysis of Global and Local Probabilistic Time Series Forecasting for Contiguous Spatial Demand Regions Finding a "Kneedle" in a Haystack: Detecting Knee Points in System Behavior

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T21:06:26.013299Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-04T21:06:24.249250Z digest=sha256:5b219d074917d65f554f1bab7ca85964dea6155919d380c12a21ede4e3fd42d0

Observation dc6a9714-d7ab-44b8-a1d1-ae32bc578cd6 · outbound

This paper cites Think Globally, Act Locally: A Deep Neural Network Approach to High-Dimensional Time Series Forecasting.

Comparative Analysis of Global and Local Probabilistic Time Series Forecasting for Contiguous Spatial Demand Regions Think Globally, Act Locally: A Deep Neural Network Approach to High-Dimensional Time Series Forecasting

Reference 36

Resolution
verified exact
local_arxiv, observed 2026-08-04T21:06:24.989979Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-04T21:06:24.293290Z digest=sha256:b1e0dab05f21c7b16c9eb253951b0675f965b97a89c06c66b8be3028f22ae8f4

Observation 628e782a-5d42-45da-acd2-e0d61e55cf77 · outbound

This paper cites Planning for Bike-sharing System: Predicting Potential Usage with Spatial Regression Models, September 2022.

Comparative Analysis of Global and Local Probabilistic Time Series Forecasting for Contiguous Spatial Demand Regions Planning for Bike-sharing System: Predicting Potential Usage with Spatial Regression Models, September 2022

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T21:06:26.001604Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-04T21:06:24.337764Z digest=sha256:c6b1b80259ac727b82d06702f5a2dada5b52a28e8b2d6cc8fa97627cc5d117f4

Observation 2fb832b8-e7da-4f33-b214-56dc9c4cd9f4 · outbound

This paper cites Optimal probabilistic forecasts for risk management.

Comparative Analysis of Global and Local Probabilistic Time Series Forecasting for Contiguous Spatial Demand Regions Optimal probabilistic forecasts for risk management

Reference 38

Resolution
verified exact
local_arxiv, observed 2026-08-04T21:06:24.870087Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-04T21:06:24.357749Z digest=sha256:19a07a44e1ebd5fd1cff50c3e2ebf206b020fd5ffb6f63cfe10fac8270f2fccc

Observation b659c400-6682-4430-be8e-925097a593ca · outbound

This paper cites Forecasting the Usage of Bike-Sharing Systems through Machine Learning Techniques to Foster Sustainable Urban Mobility.Sustainability, 16(16):6910, August 2024.

Comparative Analysis of Global and Local Probabilistic Time Series Forecasting for Contiguous Spatial Demand Regions Forecasting the Usage of Bike-Sharing Systems through Machine Learning Techniques to Foster Sustainable Urban Mobility.Sustainability, 16(16):6910, August 2024

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T21:06:25.988950Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-04T21:06:24.405585Z digest=sha256:de06118558f5776b26df3c88b29b223ed93a8e49470d768d8d64a051d1942497

Observation cce7ee31-1942-43d8-961e-6a277156e57a · outbound

This paper cites Warren Liao.

Comparative Analysis of Global and Local Probabilistic Time Series Forecasting for Contiguous Spatial Demand Regions Warren Liao

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T21:06:25.977296Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-04T21:06:24.452173Z digest=sha256:f487ddb661d01e826c05c1681a270482841fd0b1b7fc7d496f34bfad9b4756db

Observation 7a79d687-417d-43df-ac51-a78c4bf24f7f · outbound

This paper cites Wellens, Nikolaos Kourentzes, and Maximiliano Udenio.

Comparative Analysis of Global and Local Probabilistic Time Series Forecasting for Contiguous Spatial Demand Regions Wellens, Nikolaos Kourentzes, and Maximiliano Udenio

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T21:06:25.965419Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-04T21:06:24.467925Z digest=sha256:4caefb0f94be587f5bd34ea27ba068590fbd08526fd7bc69161f85fd4d9332ea

Observation 5d1f60dd-c17c-495c-9c92-fb64bbac2f60 · outbound

This paper cites Gaussian Processes for Regression.

Comparative Analysis of Global and Local Probabilistic Time Series Forecasting for Contiguous Spatial Demand Regions Gaussian Processes for Regression

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T21:06:25.954924Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-04T21:06:24.499414Z digest=sha256:5062e4582c396d6e91019785f37083c364397ff5f310ccbd7f44b93775adc4e2

Observation aabd3dd9-c41c-4175-a847-d28b33a1d47e · outbound

This paper cites Understanding the demand predictability of bike share systems: A station-level analysis.Frontiers of Engineering Management, 10(4):551–565, December 2023.

Comparative Analysis of Global and Local Probabilistic Time Series Forecasting for Contiguous Spatial Demand Regions Understanding the demand predictability of bike share systems: A station-level analysis.Frontiers of Engineering Management, 10(4):551–565, December 2023

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T21:06:25.854192Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-04T21:06:24.520970Z digest=sha256:821e0ee8102a863c3c3fc9ac8e5554fa387ce37772fc1d3ad4732e54f3bc7c82

Observation 55989766-a547-4d00-9564-7c3c84efd3c2 · outbound

This paper cites Local vs. Global Models for Hierarchical Forecasting.

Comparative Analysis of Global and Local Probabilistic Time Series Forecasting for Contiguous Spatial Demand Regions Local vs. Global Models for Hierarchical Forecasting

Reference 44

Resolution
verified exact
local_arxiv, observed 2026-08-04T21:06:24.769563Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-04T21:06:24.577914Z digest=sha256:8322aef311e70f5060641721b36ff26018baee3f9d4b3fe8386cade74475506e

Observation 88d22deb-3604-4a28-a6c5-172ea4c36b2f · outbound

This paper cites Eddy Patuwo, and Michael Y.

Comparative Analysis of Global and Local Probabilistic Time Series Forecasting for Contiguous Spatial Demand Regions Eddy Patuwo, and Michael Y

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T21:06:25.709666Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-04T21:06:24.623048Z digest=sha256:05f50986c161799409b95ea39666e21872c5f752d13363ea466e3d5398d0f715

Observation a118a179-9fa4-4ab9-938a-6af209744087 · outbound

This paper cites Deep and Confident Prediction for Time Series at Uber.

Comparative Analysis of Global and Local Probabilistic Time Series Forecasting for Contiguous Spatial Demand Regions Deep and Confident Prediction for Time Series at Uber

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T21:06:25.491738Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-04T21:06:24.656279Z digest=sha256:954082311c8ad2dfb35f88ef4375518eb69993fd63ebde3ab4b815017b666239

Observation 908c29a3-1be4-4ce4-92b4-683a4598939e · outbound

This paper cites Model-based clustering with Hidden Markov Model regression for time series with regime changes.

Comparative Analysis of Global and Local Probabilistic Time Series Forecasting for Contiguous Spatial Demand Regions Model-based clustering with Hidden Markov Model regression for time series with regime changes

Reference 2011

Resolution
verified exact
local_arxiv, observed 2026-08-04T21:06:25.301512Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-04T21:06:23.102568Z digest=sha256:efb6ca2aca01fb9b661260f12262a9f4a9057df8a05fccfb9812bf4c50aca1be

Pith citing papers

No inbound Pith citation observations are available.