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Probabilistic Reduced-Dimensional Vector Autoregressive Modeling with Oblique Projections
In this paper, we propose a probabilistic reduced-dimensional vector autoregressive (PredVAR) model to extract low-dimensional dynamics from high-dimensional noisy data.
Latent Dynamic Networked System Identification with High-Dimensional Networked Data
Networked dynamic systems are ubiquitous in various domains, such as industrial processes, social networks, and biological systems.
MLPST: MLP is All You Need for Spatio-Temporal Prediction
To accomplish the above goals, we propose an intuitive and novel framework, MLPST, a pure multi-layer perceptron architecture for traffic prediction.
On the Convergence of the Dynamic Inner PCA Algorithm
In this work, we show that this algorithm is a specialized variant of a coordinate maximization algorithm.
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