Paper Citation Record · LEDGER

Causal Adjacency Learning for Spatiotemporal Prediction Over Graphs

As of 13 August 2026, this Paper Citation Record lists 26 of 26 outbound references and 1 inbound Pith citation observation for arXiv:2411.16142.

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

pith.paper-citation-record.v1
2411.16142 v1

Coverage vector

measured 26 of 26 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T13:35:20.188187Z

measured 27 of 27 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T18:07:35.336619Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-10T18:07:35.416489Z

Reference resolution

26 of 26 outbound references displayed

verified exact0
verified fuzzy17
unresolved9
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 59f2c1ff-30e7-4b96-8e25-29eb92876dc7 · outbound

This paper cites St- gin: An uncertainty quantification approach in traffic data imputation with spatio-temporal graph attention and bidirectional recurrent united neural networks,.

Causal Adjacency Learning for Spatiotemporal Prediction Over Graphs St- gin: An uncertainty quantification approach in traffic data imputation with spatio-temporal graph attention and bidirectional recurrent united neural networks,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:35:20.491225Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 5d2089c2-d2c1-4db8-af6a-4371b07dfaa4 · outbound

This paper cites ST-MLP: A Cascaded Spatio-Temporal Linear Framework with Channel-Independence Strategy for Traffic Forecasting.

Causal Adjacency Learning for Spatiotemporal Prediction Over Graphs ST-MLP: A Cascaded Spatio-Temporal Linear Framework with Channel-Independence Strategy for Traffic Forecasting

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-12T13:35:20.082502Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cc0a401f-85d7-41c1-8b31-117e72e729f9 · outbound

This paper cites Robust node classification on graphs: Jointly from bayesian label transition and topology-based label propa- gation,.

Causal Adjacency Learning for Spatiotemporal Prediction Over Graphs Robust node classification on graphs: Jointly from bayesian label transition and topology-based label propa- gation,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:35:20.477967Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation b4ad84d5-3a16-439c-a98c-263e002f1b08 · outbound

This paper cites How does bayesian noisy self- supervision defend graph convolutional networks?.

Causal Adjacency Learning for Spatiotemporal Prediction Over Graphs How does bayesian noisy self- supervision defend graph convolutional networks?

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:35:20.465259Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation de8343d1-e763-4713-95ec-68e6b97cb2fb · outbound

This paper cites Defending graph convolutional networks against dynamic graph perturbations via bayesian self-supervision,.

Causal Adjacency Learning for Spatiotemporal Prediction Over Graphs Defending graph convolutional networks against dynamic graph perturbations via bayesian self-supervision,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:35:20.452363Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 584bbecd-7422-469a-8514-80671ccf1c4d · outbound

This paper cites Spatio-Temporal Graph Convolutional Networks: A Deep Learning Framework for Traffic Forecasting.

Causal Adjacency Learning for Spatiotemporal Prediction Over Graphs Spatio-Temporal Graph Convolutional Networks: A Deep Learning Framework for Traffic Forecasting

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-12T13:35:20.101011Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d23bdccb-3526-47df-b906-ee0cadea45d3 · outbound

This paper cites Invariant graph neural network for out-of-distribution nodes,.

Causal Adjacency Learning for Spatiotemporal Prediction Over Graphs Invariant graph neural network for out-of-distribution nodes,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:35:20.440456Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 3e18c50a-2a78-4ff3-be30-744279e0b319 · outbound

This paper cites Adaptive graph convolutional recurrent network for traffic forecasting,.

Causal Adjacency Learning for Spatiotemporal Prediction Over Graphs Adaptive graph convolutional recurrent network for traffic forecasting,

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-12T13:35:20.108668Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 00d7cea8-bd3c-496e-9e35-ebed4523f02a · outbound

This paper cites Attention based spatial-temporal graph convolutional networks for traffic flow forecast- ing,.

Causal Adjacency Learning for Spatiotemporal Prediction Over Graphs Attention based spatial-temporal graph convolutional networks for traffic flow forecast- ing,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:35:20.422367Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation cd4a6f93-4a44-4b11-8c5d-7587a4cdf862 · outbound

This paper cites Event-aware multimodal mobility nowcasting,.

Causal Adjacency Learning for Spatiotemporal Prediction Over Graphs Event-aware multimodal mobility nowcasting,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:35:20.411654Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 2bb108ad-2aed-4fb6-a3c3-b0ba415fe9e5 · outbound

This paper cites Spatiotemporal adaptive gated graph convolution network for urban traffic flow forecasting,.

Causal Adjacency Learning for Spatiotemporal Prediction Over Graphs Spatiotemporal adaptive gated graph convolution network for urban traffic flow forecasting,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:35:20.399478Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 1656a7c0-d09d-4299-8ab8-2952ff23d6cc · outbound

This paper cites Dynamic graph neural networks under spatio-temporal distribution shift,.

Causal Adjacency Learning for Spatiotemporal Prediction Over Graphs Dynamic graph neural networks under spatio-temporal distribution shift,

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-12T13:35:20.123632Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b14fbef0-2998-422a-af0a-9272d994f940 · outbound

This paper cites Deciphering spatio-temporal graph forecasting: A causal lens and treatment,.

Causal Adjacency Learning for Spatiotemporal Prediction Over Graphs Deciphering spatio-temporal graph forecasting: A causal lens and treatment,

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-12T13:35:20.127528Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ae0b7684-5993-4914-9c40-32f6e0be7269 · outbound

This paper cites Infostgcan: An information-maximizing spatial- temporal graph convolutional attention network for heterogeneous human trajectory prediction,.

Causal Adjacency Learning for Spatiotemporal Prediction Over Graphs Infostgcan: An information-maximizing spatial- temporal graph convolutional attention network for heterogeneous human trajectory prediction,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:35:20.374415Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 88b07b47-9542-456f-b555-6454e01c39a7 · outbound

This paper cites Spatial-temporal fusion graph neural networks for traffic flow forecasting,.

Causal Adjacency Learning for Spatiotemporal Prediction Over Graphs Spatial-temporal fusion graph neural networks for traffic flow forecasting,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:35:20.362803Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 6bebb205-0902-40c6-9a2e-45d718bc96cc · outbound

This paper cites Trafficgan: Network-scale deep traffic prediction with generative adversarial nets,.

Causal Adjacency Learning for Spatiotemporal Prediction Over Graphs Trafficgan: Network-scale deep traffic prediction with generative adversarial nets,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:35:20.351138Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation ca44ffbe-923c-4c9b-a133-fb855855d3dd · outbound

This paper cites Cross-and context-aware attention based spatial-temporal graph convolutional networks for human mobility prediction,.

Causal Adjacency Learning for Spatiotemporal Prediction Over Graphs Cross-and context-aware attention based spatial-temporal graph convolutional networks for human mobility prediction,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:35:20.340152Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 2d77e3dd-333d-4fb5-a93e-32fd10e85575 · outbound

This paper cites Pi-neugode: Physics-informed graph neural ordinary differential equations for spatiotemporal trajectory prediction,.

Causal Adjacency Learning for Spatiotemporal Prediction Over Graphs Pi-neugode: Physics-informed graph neural ordinary differential equations for spatiotemporal trajectory prediction,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:35:20.329388Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation baeb8874-cb71-47bd-8adf-97f4c2072d14 · outbound

This paper cites Causal imitation learn- ing via inverse reinforcement learning,.

Causal Adjacency Learning for Spatiotemporal Prediction Over Graphs Causal imitation learn- ing via inverse reinforcement learning,

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-12T13:35:20.155664Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 367d854d-35ad-458b-9da7-7d748cd24822 · outbound

This paper cites Learning causally invariant representations for out-of- distribution generalization on graphs,.

Causal Adjacency Learning for Spatiotemporal Prediction Over Graphs Learning causally invariant representations for out-of- distribution generalization on graphs,

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-12T13:35:20.162076Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 88ecc022-07b6-496b-b09c-1bc80250af29 · outbound

This paper cites Debiasing graph neural networks via learning disentangled causal substructure,.

Causal Adjacency Learning for Spatiotemporal Prediction Over Graphs Debiasing graph neural networks via learning disentangled causal substructure,

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-12T13:35:20.167159Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 293bcacb-d336-4840-b5c8-85a99c6cfad2 · outbound

This paper cites Model-powered conditional independence test,.

Causal Adjacency Learning for Spatiotemporal Prediction Over Graphs Model-powered conditional independence test,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:35:20.299296Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 2b7d4cde-060a-459b-93a4-90796ca3bdfa · outbound

This paper cites Conditional independence test for weights-of-evidence modeling,.

Causal Adjacency Learning for Spatiotemporal Prediction Over Graphs Conditional independence test for weights-of-evidence modeling,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:35:20.287143Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 0370cfb2-aa7c-43f0-91bc-04e83d24cbaa · outbound

This paper cites A permutation- based kernel conditional independence test.

Causal Adjacency Learning for Spatiotemporal Prediction Over Graphs A permutation- based kernel conditional independence test

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:35:20.272602Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 5d06ec26-12ec-42e8-ac57-c1ce06d6e39c · outbound

This paper cites Kernel-based Conditional Independence Test and Application in Causal Discovery.

Causal Adjacency Learning for Spatiotemporal Prediction Over Graphs Kernel-based Conditional Independence Test and Application in Causal Discovery

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-12T13:35:20.184021Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2f2e12a0-6f04-4fd4-a954-fca95de97599 · outbound

This paper cites Necessary and sufficient conditions for causal feature selection in time series with latent common causes,.

Causal Adjacency Learning for Spatiotemporal Prediction Over Graphs Necessary and sufficient conditions for causal feature selection in time series with latent common causes,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:35:20.255632Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Pith citing papers

Observation a2ca64df-df67-4615-9253-b91296cd1469 · inbound

Causal Learning for Heterogeneous Subgroups Based on Nonlinear Causal Kernel Clustering cites this paper.

Causal Learning for Heterogeneous Subgroups Based on Nonlinear Causal Kernel Clustering Causal Adjacency Learning for Spatiotemporal Prediction Over Graphs

Reference 46

Resolution: verified exact; local_arxiv, observed 2026-08-10T18:07:35.424182Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.