Already using NumPy, Pandas, and Scikit-learn? Here are seven more powerful data wrangling tools that deserve a place in your ...
How a NPU programming model can boost the ability to port new models onto state-of-the-art embedded silicon.
Drug–drug interactions (DDIs) present a significant challenge in clinical practice, as they may lead to adverse reactions, diminished therapeutic efficacy, and serious risks to patient safety. However ...
The graph database market, driven by AI, is growing at a rate of almost 25% annually. Graph databases support knowledge graphs, providing visual guidance for AI development. There are multiple ...
Abstract: Graph spectral filtering relies on a representation matrix to define the frequency-domain transformations. Conventional approaches use fixed graph representations, which limit their ...
Abstract: Graph neural networks (GNNs) have achieved remarkable success in learning graph representations, especially graph Transformers, which have recently shown superior performance on various ...
Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. Non-Commercial (NC): Only non-commercial uses of the work are permitted. In ...
Physics and Python stuff. Most of the videos here are either adapted from class lectures or solving physics problems. I really like to use numerical calculations without all the fancy programming ...
Veloclade is a research prototype of a neuro-symbolic knowledge graph system. It uses clade-inspired hierarchy + embedding clustering (sentence-transformers) to control ontology growth and mitigate ...
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