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ARMA GNN

ARMA

38 papers tagged archive 2025-07-28

Introduced by Filippo Maria Bianchi et al. in Graph Neural Networks with convolutional ARMA filters

archive 2025-07-28 Description, source and code snippet are the archive's method entry.

The ARMA GNN layer implements a rational graph filter with a recursive approximation.

PaperSource

Papers archive 2025-07-28

30 shown of 38, newest first. Repository counts are the archive's code-links table. A Syntology line states what Syntology ran from that paper's harvested code; it is per sample and not a correctness claim.

Tasks archive 2025-07-28

20 shown of 41 tasks the archive attaches to papers tagged with this method, by distinct papers. A task without a page in the catalog is plain text.

TaskPapers
Time Series11
Time Series Analysis9
Management4
regression4
Prediction3
Time Series Forecasting3
Model Predictive Control2
model2
Anomaly Detection1
BIG-bench Machine Learning1
Bayesian Optimization1
Classification1
Decoder1
Deep Learning1
Demand Forecasting1
Descriptive1
Feature Engineering1
Future prediction1
General Classification1
Graph Classification1

Usage over time archive 2025-07-28

Papers per year tagged with ARMA: 2019 to 2025, peak 7 7 0 2019: 7 papers 2019 2020: 5 papers 2020 2021: 6 papers 2021 2022: 4 papers 2022 2023: 7 papers 2023 2024: 6 papers 2024 2025: 3 papers 2025
Papers per year the archive tags with this method, by the paper's archive date (38 dated). Bars are counts, not a trend claim.

Components: the archive holds no method-to-method composition, so PwC's Components table cannot be rebuilt; the Papers list carries no Results column for the same reason (the archive does not join its leaderboard rows to method tags).

Categories archive 2025-07-28

Graph Models

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