Current semi-supervised graph classification methods, such as those based on pseudo-labels and knowledge distillation, still face limitations in effectively utilizing unlabeled graph data and ...

To tackle these challenges, we propose a novel framework called AISFuser to i) encode unique maritime traffic network into graphical representations, and ii) introduce the heterogeneity into ...

Therefore, it is of great significance to design a computational model with high efficiency and accuracy. In this paper, we propose a novel computational method MGRL to predict drug-disease ...

This method utilizes Neumann series of Bessel function representations ... by reducing it to a two-spectra inverse Sturm-Liouville problem on each edge of the graph, leading to a system of linear ...

Inverse problems in fractional differential ... challenge of recovering a space-dependent source term in a third-order pseudo-parabolic equation. This research highlighted the ill-posed nature ...

Our goal is to build a high-performance Knowledge Graph tailored for Large Language Models (LLMs), prioritizing exceptionally low latency to ensure fast and efficient information delivery through our ...

The management of Leishmania donova ni (LD), responsible for fatal visceral leishmaniasis (VL), faces increasing challenges due to rising drug-unresponsiveness, leading to increasing treatment ...

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Figure 1. Example of weakly-stationary and non-stationary signals generated using auto-regressive fractionally integrated moving-average (ARFIMA) processes (see Simulated time series). The mean and ...

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