Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-07T21:26:16.920522Z
Paper Citation Record · LEDGER
Learning to Predict Global Atrial Fibrillation Dynamics from Sparse Measurements
As of 23 August 2026, this Paper Citation Record lists 72 of 72 outbound references and 0 inbound Pith citation observations for arXiv:2502.09473.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
Reference resolution
72 of 72 outbound references displayed
- verified exact0
- verified fuzzy63
- unresolved8
- parse uncertain0
- malformed identifier1
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation e217b78c-44e5-4fef-b735-5e3dfd3fdb97 · outbound
This paper cites Lifetime risk of atrial fibrillation by race and socioeconomic status: ARIC study (Atherosclerosis Risk in Communities).
Learning to Predict Global Atrial Fibrillation Dynamics from Sparse Measurements Lifetime risk of atrial fibrillation by race and socioeconomic status: ARIC study (Atherosclerosis Risk in Communities)
Reference 1
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T21:26:18.192201Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 4d747394-6b7d-432d-9f3a-206e361eebea · outbound
This paper cites Global epidemiology of atrial fibrillation: An increasing epidemic and public health challenge.
Learning to Predict Global Atrial Fibrillation Dynamics from Sparse Measurements Global epidemiology of atrial fibrillation: An increasing epidemic and public health challenge
Reference 2
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T21:26:18.176907Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation b581d9a8-3878-48f3-8c57-5a751591663c · outbound
This paper cites Stroke prevention in atrial fibrillation: Looking forward.
Learning to Predict Global Atrial Fibrillation Dynamics from Sparse Measurements Stroke prevention in atrial fibrillation: Looking forward
Reference 3
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T21:26:18.161377Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 89b30c6e-e891-4b58-a80d-1e8d5d39f0cc · outbound
This paper cites Atrial fibrillation in heart failure: Epidemiology, pathophysiology, and rationale for therapy.
Learning to Predict Global Atrial Fibrillation Dynamics from Sparse Measurements Atrial fibrillation in heart failure: Epidemiology, pathophysiology, and rationale for therapy
Reference 4
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T21:26:18.145286Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation cd3a1696-8e75-4c47-a277-3b54e22a93fa · outbound
This paper cites Impact of atrial fibrillation on mortality, stroke, and medical costs.
Learning to Predict Global Atrial Fibrillation Dynamics from Sparse Measurements Impact of atrial fibrillation on mortality, stroke, and medical costs
Reference 5
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T21:26:18.129154Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 951afd73-9169-417a-8c0e-e56fd35564cc · outbound
This paper cites Cost of an emerging epidemic: An economic analysis of atrial fibrillation in the UK.
Learning to Predict Global Atrial Fibrillation Dynamics from Sparse Measurements Cost of an emerging epidemic: An economic analysis of atrial fibrillation in the UK
Reference 6
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T21:26:18.114209Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation d501f69a-a866-45de-bf86-9ef0dd6c6fb5 · outbound
This paper cites Atrial fibrillation burden and clinical outcomes in heart failure: The CASTLE-AF trial.
Learning to Predict Global Atrial Fibrillation Dynamics from Sparse Measurements Atrial fibrillation burden and clinical outcomes in heart failure: The CASTLE-AF trial
Reference 7
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T21:26:18.098145Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 9bc04046-418a-47a5-975d-b4fb79783df4 · outbound
This paper cites an unresolved cited work.
Learning to Predict Global Atrial Fibrillation Dynamics from Sparse Measurements Unresolved cited work
Reference 8
- Resolution
- unresolved
- raw_fallback, observed 2026-08-07T21:26:18.082920Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 04149d2d-a2df-4056-96f7-f2fd3effd32f · outbound
This paper cites Cryoballoon or radiofrequency ablation for paroxysmal atrial fibrillation.
Learning to Predict Global Atrial Fibrillation Dynamics from Sparse Measurements Cryoballoon or radiofrequency ablation for paroxysmal atrial fibrillation
Reference 9
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T21:26:18.068013Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 52a69be1-7b17-4cd7-8781-a60899afbe74 · outbound
This paper cites Five-year outcome of catheter ablation of persistent atrial fibrillation using termination of atrial fibrillation as a procedural endpoint.
Learning to Predict Global Atrial Fibrillation Dynamics from Sparse Measurements Five-year outcome of catheter ablation of persistent atrial fibrillation using termination of atrial fibrillation as a procedural endpoint
Reference 10
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T21:26:18.048799Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 10639a52-a38f-4b97-ae79-c99efe11ec79 · outbound
This paper cites The electrical isolation of the left atrial posterior wall in catheter ablation of persistent atrial fibrillation.
Learning to Predict Global Atrial Fibrillation Dynamics from Sparse Measurements The electrical isolation of the left atrial posterior wall in catheter ablation of persistent atrial fibrillation
Reference 11
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T21:26:18.033320Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation de6d4a6d-72f9-42fd-aa4e-d7bff5d3fb4c · outbound
This paper cites Approaches to catheter ablation for persistent atrial fibrillation.
Learning to Predict Global Atrial Fibrillation Dynamics from Sparse Measurements Approaches to catheter ablation for persistent atrial fibrillation
Reference 12
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T21:26:18.016052Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 02345e7c-2f21-4aae-9be2-a919c25d33f4 · outbound
This paper cites Pulmonary vein isolation versus defragmentation: The CHASE-AF clinical trial.
Learning to Predict Global Atrial Fibrillation Dynamics from Sparse Measurements Pulmonary vein isolation versus defragmentation: The CHASE-AF clinical trial
Reference 13
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T21:26:17.997004Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation b43d98a2-3752-4e2c-b4ba-7165e5bc2172 · outbound
This paper cites Narayan et al.
Learning to Predict Global Atrial Fibrillation Dynamics from Sparse Measurements Narayan et al
Reference 14
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T21:26:17.981395Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 3529a1b2-5b13-44cc-8920-c07c739c4901 · outbound
This paper cites No benefit of complex fractionated atrial electrogram ablation in addition to circumferential pulmonary vein ablation and linear ablation: Benefit of complex ablation study.
Learning to Predict Global Atrial Fibrillation Dynamics from Sparse Measurements No benefit of complex fractionated atrial electrogram ablation in addition to circumferential pulmonary vein ablation and linear ablation: Benefit of complex ablation study
Reference 15
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T21:26:17.966272Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 28b708fb-28f8-4112-9ef5-e1aab4fce9a5 · outbound
This paper cites Toward mechanism-directed electrophenotype-based treatments for atrial fibrillation.
Learning to Predict Global Atrial Fibrillation Dynamics from Sparse Measurements Toward mechanism-directed electrophenotype-based treatments for atrial fibrillation
Reference 16
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T21:26:17.950344Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation abf42888-dd5d-404f-9486-d5a7cea2df1a · outbound
This paper cites High-density and high coverage composite mapping of repetitive atrial activation patterns.
Learning to Predict Global Atrial Fibrillation Dynamics from Sparse Measurements High-density and high coverage composite mapping of repetitive atrial activation patterns
Reference 17
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T21:26:17.934998Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation ca6774f0-97c4-4118-a0ef-cd172a036bff · outbound
This paper cites Long-term clinical outcomes of focal impulse and rotor modulation for treatment of atrial fibrillation: A multicenter experience.
Learning to Predict Global Atrial Fibrillation Dynamics from Sparse Measurements Long-term clinical outcomes of focal impulse and rotor modulation for treatment of atrial fibrillation: A multicenter experience
Reference 18
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T21:26:17.919623Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 0232edb9-7e51-4f64-b2c5-c5c95151a10d · outbound
This paper cites Noninvasive electrocardiographic imaging.
Learning to Predict Global Atrial Fibrillation Dynamics from Sparse Measurements Noninvasive electrocardiographic imaging
Reference 19
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T21:26:17.904405Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation d7d3a64a-d5a4-42cb-984b-7ad00f09871b · outbound
This paper cites Spatial resolution requirements for accurate identification of drivers of atrial fibrillation.
Learning to Predict Global Atrial Fibrillation Dynamics from Sparse Measurements Spatial resolution requirements for accurate identification of drivers of atrial fibrillation
Reference 20
- Resolution
- malformed identifier
- raw_fallback, observed 2026-08-07T21:26:17.889893Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 0a8f6f91-07b2-481b-85a4-7ba6374ca794 · outbound
This paper cites Synchronization of pulse-coupled biological oscillators.
Learning to Predict Global Atrial Fibrillation Dynamics from Sparse Measurements Synchronization of pulse-coupled biological oscillators
Reference 21
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T21:26:17.873561Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 0c5c32ab-b55b-4956-a1cd-b04ed7eb4126 · outbound
This paper cites The fundamental organization of cardiac mitochondria as a network of coupled oscillators.
Learning to Predict Global Atrial Fibrillation Dynamics from Sparse Measurements The fundamental organization of cardiac mitochondria as a network of coupled oscillators
Reference 22
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T21:26:17.857779Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation ee4f8d50-03d8-4664-8623-52e48617f8c7 · outbound
This paper cites Nonlinear and stochastic dynamics in the heart.
Learning to Predict Global Atrial Fibrillation Dynamics from Sparse Measurements Nonlinear and stochastic dynamics in the heart
Reference 23
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T21:26:17.841803Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation f609b744-6e6e-4072-862b-b4280fb2899b · outbound
This paper cites The graph neural network model.
Learning to Predict Global Atrial Fibrillation Dynamics from Sparse Measurements The graph neural network model
Reference 24
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T21:26:17.826688Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 46d8cc3d-d637-4c89-b510-75aec8551450 · outbound
This paper cites Geometric deep learning: Going beyond Euclidean data.
Learning to Predict Global Atrial Fibrillation Dynamics from Sparse Measurements Geometric deep learning: Going beyond Euclidean data
Reference 25
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T21:26:17.812087Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 7148f6c7-5bf0-4cea-8b18-a1df20a5ab29 · outbound
This paper cites A gentle introduction to deep learning for graphs.
Learning to Predict Global Atrial Fibrillation Dynamics from Sparse Measurements A gentle introduction to deep learning for graphs
Reference 26
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T21:26:17.797665Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 0571e587-e2c9-4ee3-9708-52ad9267c036 · outbound
This paper cites Structured sequence modeling with graph convolutional recurrent networks.
Learning to Predict Global Atrial Fibrillation Dynamics from Sparse Measurements Structured sequence modeling with graph convolutional recurrent networks
Reference 27
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T21:26:17.782404Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 018e5b30-6d63-4aae-a8e1-1dd2719ea327 · outbound
This paper cites Filling the g_ap_s: Multivariate time series imputation by graph neural networks.
Learning to Predict Global Atrial Fibrillation Dynamics from Sparse Measurements Filling the g_ap_s: Multivariate time series imputation by graph neural networks
Reference 28
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T21:26:17.766752Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 44d57024-f847-4e75-839e-9063a725a2ab · outbound
This paper cites Word embedding for understanding natural language: A survey.
Learning to Predict Global Atrial Fibrillation Dynamics from Sparse Measurements Word embedding for understanding natural language: A survey
Reference 29
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T21:26:17.750913Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 60cfe5b8-3211-43ec-9050-e2f102e61666 · outbound
This paper cites an unresolved cited work.
Learning to Predict Global Atrial Fibrillation Dynamics from Sparse Measurements Unresolved cited work
Reference 30
- Resolution
- unresolved
- raw_fallback, observed 2026-08-07T21:26:17.735174Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 92444e3c-aab6-4da5-be28-e0cc27666b21 · outbound
This paper cites Validation of dipole density mapping during atrial fibrillation and sinus rhythm in human left atrium.
Learning to Predict Global Atrial Fibrillation Dynamics from Sparse Measurements Validation of dipole density mapping during atrial fibrillation and sinus rhythm in human left atrium
Reference 31
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T21:26:17.720422Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 3faed7d9-c8cb-49d5-8b82-d26c172fb237 · outbound
This paper cites Standardised framework for quantitative analysis of fibrillation dynamics.
Learning to Predict Global Atrial Fibrillation Dynamics from Sparse Measurements Standardised framework for quantitative analysis of fibrillation dynamics
Reference 32
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T21:26:17.704677Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 34767c37-4f46-4e5e-a795-1f0903ab1cee · outbound
This paper cites Visualizing data using t-SNE.
Learning to Predict Global Atrial Fibrillation Dynamics from Sparse Measurements Visualizing data using t-SNE
Reference 33
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T21:26:17.689490Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 4d6a8147-9a06-49ae-ab80-b1abaca7b7e9 · outbound
This paper cites Recurrence plots for the analysis of complex systems.
Learning to Predict Global Atrial Fibrillation Dynamics from Sparse Measurements Recurrence plots for the analysis of complex systems
Reference 34
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T21:26:17.673720Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 62c0b627-e587-45c1-b5b7-9df785834289 · outbound
This paper cites V ortex dynamics in three-dimensional continuous myocardium with fiber rotation: Filament instability and fibrillation.
Learning to Predict Global Atrial Fibrillation Dynamics from Sparse Measurements V ortex dynamics in three-dimensional continuous myocardium with fiber rotation: Filament instability and fibrillation
Reference 35
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T21:26:17.657095Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 3556f9a9-ef4d-422c-a312-2eadc9f96477 · outbound
This paper cites Models of cardiac tissue electrophysiology: Progress, challenges and open questions.
Learning to Predict Global Atrial Fibrillation Dynamics from Sparse Measurements Models of cardiac tissue electrophysiology: Progress, challenges and open questions
Reference 36
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T21:26:17.641244Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 8dab83ec-0d21-4daa-b198-ca83cf4debc9 · outbound
This paper cites Graph-based time series clustering for end-to-end hierarchical forecasting.
Learning to Predict Global Atrial Fibrillation Dynamics from Sparse Measurements Graph-based time series clustering for end-to-end hierarchical forecasting
Reference 37
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T21:26:17.624639Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 7d6b6672-5dc3-4485-abbe-a2d74c2b732c · outbound
This paper cites Learning to reconstruct missing data from spatiotemporal graphs with sparse observations.
Learning to Predict Global Atrial Fibrillation Dynamics from Sparse Measurements Learning to reconstruct missing data from spatiotemporal graphs with sparse observations
Reference 38
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T21:26:17.608994Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 140f0832-1485-42ad-8f08-8a4500598c09 · outbound
This paper cites Graph signal processing: Overview, challenges, and applications.
Learning to Predict Global Atrial Fibrillation Dynamics from Sparse Measurements Graph signal processing: Overview, challenges, and applications
Reference 39
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T21:26:17.592984Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation fe881b69-35e2-4ae2-90d5-2a6c7bebf29f · outbound
This paper cites Data analytics on graphs. Part II: Signals on graphs.
Learning to Predict Global Atrial Fibrillation Dynamics from Sparse Measurements Data analytics on graphs. Part II: Signals on graphs
Reference 40
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T21:26:17.528705Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 2c9c9811-50b3-4dc9-b211-27a8b1cda53c · outbound
This paper cites Data analytics on graphs. Part III: Machine learning on graphs, from graph topology to applications.
Learning to Predict Global Atrial Fibrillation Dynamics from Sparse Measurements Data analytics on graphs. Part III: Machine learning on graphs, from graph topology to applications
Reference 41
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T21:26:17.488192Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 938523c3-2179-4e26-a5bf-62185b2b0734 · outbound
This paper cites Semi-supervised classification with graph convolutional networks.
Learning to Predict Global Atrial Fibrillation Dynamics from Sparse Measurements Semi-supervised classification with graph convolutional networks
Reference 42
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T21:26:17.472579Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation a7d9179b-b47f-4270-abe0-374d4fcd8ada · outbound
This paper cites Deep learning on graphs: A survey.
Learning to Predict Global Atrial Fibrillation Dynamics from Sparse Measurements Deep learning on graphs: A survey
Reference 43
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T21:26:17.457279Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 9f53eb21-5b8c-4fae-b961-c9bb5c4187d5 · outbound
This paper cites Graph Deep Learning for Time Series Forecasting.
Learning to Predict Global Atrial Fibrillation Dynamics from Sparse Measurements Graph Deep Learning for Time Series Forecasting
Reference 44
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T21:26:16.767377Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 6b4803ce-a26a-4bba-a03a-e4ce20e47558 · outbound
This paper cites A survey on graph neural networks for time series: Forecasting, classification, imputation, and anomaly detection.
Learning to Predict Global Atrial Fibrillation Dynamics from Sparse Measurements A survey on graph neural networks for time series: Forecasting, classification, imputation, and anomaly detection
Reference 45
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T21:26:17.440899Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation ff47e89a-28d9-4558-a8f4-2f05267ddfb6 · outbound
This paper cites On the equivalence between temporal and static equivariant graph representations.
Learning to Predict Global Atrial Fibrillation Dynamics from Sparse Measurements On the equivalence between temporal and static equivariant graph representations
Reference 46
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T21:26:17.424946Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 03b43292-9d5b-4823-8536-c22795f64aee · outbound
This paper cites Scalable spatiotemporal graph neural networks.
Learning to Predict Global Atrial Fibrillation Dynamics from Sparse Measurements Scalable spatiotemporal graph neural networks
Reference 47
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T21:26:17.401722Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 67798dd0-e3f5-452a-8b9c-bd4bd991d58b · outbound
This paper cites Diffusion convolutional recurrent neural network: Data-driven traffic forecasting.
Learning to Predict Global Atrial Fibrillation Dynamics from Sparse Measurements Diffusion convolutional recurrent neural network: Data-driven traffic forecasting
Reference 48
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T21:26:17.385526Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 9d465f91-c511-4669-918c-680442ed3b32 · outbound
This paper cites Graph neural network for traffic forecasting: A survey.
Learning to Predict Global Atrial Fibrillation Dynamics from Sparse Measurements Graph neural network for traffic forecasting: A survey
Reference 49
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T21:26:17.369254Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 20568478-cb3e-4dbd-995b-d08e8d7bd00c · outbound
This paper cites Learning skillful medium-range global weather forecasting.
Learning to Predict Global Atrial Fibrillation Dynamics from Sparse Measurements Learning skillful medium-range global weather forecasting
Reference 50
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T21:26:17.354071Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation cb073b49-1f8c-4397-9a00-5057d0143c5e · outbound
This paper cites Taming local effects in graph-based spatiotemporal forecasting.
Learning to Predict Global Atrial Fibrillation Dynamics from Sparse Measurements Taming local effects in graph-based spatiotemporal forecasting
Reference 51
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T21:26:17.337820Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 430ddccb-e6ef-4d23-b5db-bc0d996cacf2 · outbound
This paper cites NodeTrans: A Graph Transfer Learning Approach for Traffic Prediction.
Learning to Predict Global Atrial Fibrillation Dynamics from Sparse Measurements NodeTrans: A Graph Transfer Learning Approach for Traffic Prediction
Reference 52
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T21:26:16.809356Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 90e22ec2-1c3c-4e9b-a268-3cf2ffb633a2 · outbound
This paper cites Bayesian probabilistic matrix factorization using Markov chain Monte Carlo.
Learning to Predict Global Atrial Fibrillation Dynamics from Sparse Measurements Bayesian probabilistic matrix factorization using Markov chain Monte Carlo
Reference 53
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T21:26:17.321463Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 6e495288-5568-4465-8f05-0ae92396d3b5 · outbound
This paper cites Algorithms for non-negative matrix factorization.
Learning to Predict Global Atrial Fibrillation Dynamics from Sparse Measurements Algorithms for non-negative matrix factorization
Reference 54
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T21:26:17.304195Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 1d502099-73f0-4bea-9363-7ff59429b243 · outbound
This paper cites Graph regularized nonnegative matrix factorization for data representation.
Learning to Predict Global Atrial Fibrillation Dynamics from Sparse Measurements Graph regularized nonnegative matrix factorization for data representation
Reference 55
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T21:26:17.287705Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 56ede9c5-1766-4c5a-ac80-07cfdd146d4e · outbound
This paper cites Temporal regularized matrix factorization for high-dimensional time series prediction.
Learning to Predict Global Atrial Fibrillation Dynamics from Sparse Measurements Temporal regularized matrix factorization for high-dimensional time series prediction
Reference 56
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T21:26:17.271233Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 8ccba2cd-601b-49e2-ad21-6bba8c71b94e · outbound
This paper cites BRITS: Bidirectional recurrent imputation for time series.
Learning to Predict Global Atrial Fibrillation Dynamics from Sparse Measurements BRITS: Bidirectional recurrent imputation for time series
Reference 57
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T21:26:17.254424Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 3c5f93b0-5b26-43b1-b358-f7963a9c4308 · outbound
This paper cites Time-series generative adversarial networks.
Learning to Predict Global Atrial Fibrillation Dynamics from Sparse Measurements Time-series generative adversarial networks
Reference 58
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T21:26:17.237870Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 598f5c9b-1488-4e3e-b9dd-125dfe252d5f · outbound
This paper cites NAOMI: Non-autoregressive multiresolution sequence imputation.
Learning to Predict Global Atrial Fibrillation Dynamics from Sparse Measurements NAOMI: Non-autoregressive multiresolution sequence imputation
Reference 59
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T21:26:17.221556Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 753581bd-8bfe-4def-b634-c85dc2254ea2 · outbound
This paper cites SAITS: Self-attention-based imputation for time series.
Learning to Predict Global Atrial Fibrillation Dynamics from Sparse Measurements SAITS: Self-attention-based imputation for time series
Reference 60
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T21:26:17.205100Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 764e54b1-67d4-4ee1-be20-fcf6a13fd5f3 · outbound
This paper cites CSDI: Conditional score-based diffusion models for probabilistic time series imputation.
Learning to Predict Global Atrial Fibrillation Dynamics from Sparse Measurements CSDI: Conditional score-based diffusion models for probabilistic time series imputation
Reference 61
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T21:26:17.188650Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 4187c99a-df05-4d3b-bc5d-921ee4ce9e36 · outbound
This paper cites Diffusion-based time series imputation and forecasting with structured state space models.
Learning to Predict Global Atrial Fibrillation Dynamics from Sparse Measurements Diffusion-based time series imputation and forecasting with structured state space models
Reference 62
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T21:26:17.170933Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 385c746d-f16e-4b93-94ee-8f36efc9e7b1 · outbound
This paper cites Improving Diffusion Models for ECG Imputation with an Augmented Template Prior.
Learning to Predict Global Atrial Fibrillation Dynamics from Sparse Measurements Improving Diffusion Models for ECG Imputation with an Augmented Template Prior
Reference 63
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T21:26:16.863257Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 541acb7e-ab85-4b0f-91d6-16bf282ca22f · outbound
This paper cites Principles and algorithms for forecasting groups of time series: Locality and globality.
Learning to Predict Global Atrial Fibrillation Dynamics from Sparse Measurements Principles and algorithms for forecasting groups of time series: Locality and globality
Reference 64
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T21:26:17.152199Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 3aca7c53-e87d-4228-8850-27fac98ef3ea · outbound
This paper cites Residual Gated Graph ConvNets.
Learning to Predict Global Atrial Fibrillation Dynamics from Sparse Measurements Residual Gated Graph ConvNets
Reference 65
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T21:26:16.875312Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 9888efaa-2a2e-4795-b991-2ddfd7bf157c · outbound
This paper cites Diffusion-convolutional neural networks.
Learning to Predict Global Atrial Fibrillation Dynamics from Sparse Measurements Diffusion-convolutional neural networks
Reference 66
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T21:26:17.135958Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 2799ed74-47c7-4b1d-bdb7-7a19cfd27af0 · outbound
This paper cites Quantile regression.
Learning to Predict Global Atrial Fibrillation Dynamics from Sparse Measurements Quantile regression
Reference 67
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T21:26:17.120131Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation c66ff37b-1458-43a8-9f66-7a839365cfda · outbound
This paper cites Laplacian eigenmaps for dimensionality reduction and data representation.
Learning to Predict Global Atrial Fibrillation Dynamics from Sparse Measurements Laplacian eigenmaps for dimensionality reduction and data representation
Reference 68
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T21:26:17.102760Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 444847be-15df-499b-802a-b54139339877 · outbound
This paper cites Method for registration of 3-D shapes.
Learning to Predict Global Atrial Fibrillation Dynamics from Sparse Measurements Method for registration of 3-D shapes
Reference 69
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T21:26:17.085939Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation db4f455e-85f7-446e-adf8-4a0bd23e30e0 · outbound
This paper cites an unresolved cited work.
Learning to Predict Global Atrial Fibrillation Dynamics from Sparse Measurements Unresolved cited work
Reference 70
- Resolution
- unresolved
- raw_fallback, observed 2026-08-07T21:26:17.070043Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 286da05b-7d20-49ed-80d6-0c7cff01adfa · outbound
This paper cites an unresolved cited work.
Learning to Predict Global Atrial Fibrillation Dynamics from Sparse Measurements Unresolved cited work
Reference 71
- Resolution
- unresolved
- raw_fallback, observed 2026-08-07T21:26:17.055148Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 5ac8b1ae-6b36-45c7-bf92-ab763f2e41dd · outbound
This paper cites Mean and MF baseline models are employed solely on the test set due to their transductive nature.
Learning to Predict Global Atrial Fibrillation Dynamics from Sparse Measurements Mean and MF baseline models are employed solely on the test set due to their transductive nature
Reference 72
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T21:26:17.040013Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Pith citing papers
No inbound Pith citation observations are available.