On the public citation graph

Spatiotemporal Synchronous Multiscale Frequency-Domain Hypergraph Convolutional Network for Traffic Flow Predictions

https://doi.org/10.2139/ssrn.7451141
0 signed · 14 inferred · view as graph

Inferred edges come from two machine sources: sweeps of open repository metadata (mostly SSRN and Zenodo), and a bulk OpenAlex citation snapshot. Every row below is labelled with the one it came from. Neither is a complete citation index — absence here is not evidence of absence.

Is this your work? Sign in with ORCID and put your name on the claims that are yours.
Claim with ORCID
Reference health. See whether every reference in this work resolves to a known work and none has been retracted — and get a dated CiteStamped badge you can embed.
See reference health

What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1016/j.asoc.2025.112979openalex-snapshot
Dynamic trend fusion module for traffic flow prediction
inferredcites →https://doi.org/10.1016/j.inffus.2023.102146openalex-snapshot
Traffic flow matrix-based graph neural network with attention mechanism for traffic flow prediction
inferredcites →https://doi.org/10.1080/01441647.2018.1442887openalex-snapshot
Spatiotemporal traffic forecasting: review and proposed directions
inferredcites →https://doi.org/10.1109/72.279188openalex-snapshot
Recurrent neural networks and robust time series prediction
inferredcites →https://doi.org/10.1109/jas.2023.123033openalex-snapshot
STGSA: A Novel Spatial-Temporal Graph Synchronous Aggregation Model for Traffic Prediction
inferredcites →https://doi.org/10.1109/tpami.2023.3331389openalex-snapshot
Messages are Never Propagated Alone: Collaborative Hypergraph Neural Network for Time-Series Forecasting
inferredcites →https://doi.org/10.1111/j.1553-2712.1998.tb02493.xopenalex-snapshot
Time Series Analysis Using Autoregressive Integrated Moving Average (ARIMA) Models
inferredcites →https://doi.org/10.1145/3394486.3403389openalex-snapshot
Hypergraph Convolutional Recurrent Neural Network
inferredcites →https://doi.org/10.1145/3557918.3565866openalex-snapshot
SHGCN
inferredcites →https://doi.org/10.1162/neco.1997.9.8.1735openalex-snapshot
Long Short-Term Memory
inferredcites →https://doi.org/10.1609/aaai.v33i01.3301922openalex-snapshot
Attention Based Spatial-Temporal Graph Convolutional Networks for Traffic Flow Forecasting
inferredcites →https://doi.org/10.1609/aaai.v34i01.5438openalex-snapshot
Spatial-Temporal Synchronous Graph Convolutional Networks: A New Framework for Spatial-Temporal Network Data Forecasting
inferredcites →https://doi.org/10.1609/aaai.v35i5.16542openalex-snapshot
Spatial-Temporal Fusion Graph Neural Networks for Traffic Flow Forecasting
inferredcites →https://doi.org/10.52202/079017-1050openalex-snapshot
Ada-MSHyper: Adaptive Multi-Scale Hypergraph Transformer for Time Series Forecasting
Editorial review for independent work. ICSAC — the Institute for Complexity Science and Advanced Computing — runs a structured editorial panel for researchers publishing outside journals, and publishes on CiteStamp rails. Submission is free and goes through ORCID: icsacinstitute.org/submit.