Abstract: In this work, we propose a continuous neural network architecture, referred to as Explainable Tensorized Neural - Ordinary Differential Equations (ETN-ODE) network for multi-step time series ...
Abstract: Subspace clustering has been successful in unsupervised learning by revealing low-dimensional structures in high-dimensional data. However, most existing subspace clustering methods rely on ...
Approach. In this paper, we propose a MUDA method, Tensorized Spatial-Frequency Attention Network (TSFAN), to assist the performance of the target domain for EEG-based biometric recognition.
Tensorized layers (CP, Tucker, TensorTrain, and TensorRing) are more efficient and have also been shown to act as regularizers. One natural extension is using Tensorized layers to parameterize the ...
Since hand-print recognition, i.e., palmprint, finger-knuckle-print (FKP), and hand-vein, have significant superiority in user convenience and hygiene, it has attracted greater enthusiasm from ...
Ant Colony Optimization (ACO) is renowned for its effectiveness in solving Traveling Salesman Problems, yet it faces computational challenges in CPU-based environments, particularly with large-scale ...
Graph Neural Networks (GNNs) have demonstrated significant potential as powerful tools for handling graph data in various fields. However, traditional GNNs often encounter limitations in information ...
Sam Mugel, Ph.D., is the CTO of Multiverse Computing, a global leader in developing value-driven quantum solutions for businesses. Carbon emissions continue to plague the planet’s climate and endanger ...
Sam Mugel, Ph.D., is the CTO of Multiverse Computing, a global leader in developing value-driven quantum solutions for businesses. Quantum mechanics, which is the study of the behavior of sub-atomic ...
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