Description
The ARMA GNN layer implements a rational graph filter with a recursive approximation.
Papers Using This Method
Intraday Functional PCA Forecasting of Cryptocurrency Returns2025-05-26On the Importance of Clearsky Model in Short-Term Solar Radiation Forecasting2025-03-06GRAMA: Adaptive Graph Autoregressive Moving Average Models2025-01-22MPC-guided, Data-driven Fuzzy Controller Synthesis2024-10-09Autoregressive Moving-average Attention Mechanism for Time Series Forecasting2024-10-04On the Approximability of Stationary Processes using the ARMA Model2024-08-20Interval Forecasts for Gas Prices in the Face of Structural Breaks -- Statistical Models vs. Neural Networks2024-07-23Research on Credit Risk Early Warning Model of Commercial Banks Based on Neural Network Algorithm2024-05-17Rate-Optimal Non-Asymptotics for the Quadratic Prediction Error Method2024-04-11SALSA: Sequential Approximate Leverage-Score Algorithm with Application in Analyzing Big Time Series Data2023-12-30Predicting Temperature of Major Cities Using Machine Learning and Deep Learning2023-09-23Overlapping Batch Confidence Intervals on Statistical Functionals Constructed from Time Series: Application to Quantiles, Optimization, and Estimation2023-07-17Distributed detection of ARMA signals2023-04-14Electricity Demand Forecasting with Hybrid Statistical and Machine Learning Algorithms: Case Study of Ukraine2023-04-11Learning Graph ARMA Processes from Time-Vertex Spectra2023-02-14Machine Learning Approach and Extreme Value Theory to Correlated Stochastic Time Series with Application to Tree Ring Data2023-01-27An Information-State Based Approach to Linear Time Varying System Identification and Control2022-11-19ARMA Cell: A Modular and Effective Approach for Neural Autoregressive Modeling2022-08-31Forecasting foreign exchange rates with regression networks tuned by Bayesian optimization2022-04-26High-dimensional dynamic factor models: a selective survey and lines of future research2022-02-15