Traditional computational electromagnetics (CEM) methods—such as MoM, FEM, or FDTD—offer high fidelity, but struggle to scale ...

Abstract: Despite advancements using graph neural networks (GNNs) to capture complex user-item interactions, challenges persist due to data sparsity and noise. To address these, self-supervised ...

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. EncoderMap is a dimensionality reduction method that is tailored for the analysis of ...

The Supporting Information is available free of charge at https://pubs.acs.org/doi/10.1021/acs.jcim.5c01525. Efficiency analysis of different normalization strategies ...

Traffic prediction is the core of intelligent transportation system, and accurate traffic speed prediction is the key to optimize traffic management. Currently, the traffic speed prediction model ...

Abstract: The increasing complexity of Analog/Mixed-Signal (AMS) schematics has been posing significant challenges in structure recognition, particularly in the intellectual property (IP) industry, ...

If you have a health insurance plan, you’ve probably come across the terms “in-network” and “out-of-network.” Simply put, in-network means the doctors or hospitals you visit contract with your ...

The clock started ticking when Michelle Mazzola’s son, Guy, was diagnosed with autism before his second birthday. Doctors told her the sooner Guy received therapy for his nonverbal communication and ...

The high-performance networking market has long been dominated by two primary architectures: Ethernet, originally designed for general-purpose networking more than 50 years ago, and InfiniBand, ...

According to mathematical legend, Peter Sarnak and Noga Alon made a bet about optimal graphs in the late 1980s. They’ve now both been proved wrong. It started with a bet. In the late 1980s, at a ...