Abstract: Gaussian processes (GPs) stand as crucial tools in machine learning and signal processing, with their effectiveness hinging on kernel design and hyperparameter optimization. This article ...
School of Materials Science and Engineering, Beihang University, Beijing 100191, China State Key Laboratory of Artificial Intelligence for Materials Science, Beihang University, Beijing 100091, China ...
Neural networks revolutionized machine learning for classical computers: self-driving cars, language translation and even artificial intelligence software were all made possible. It is no wonder, then ...
NVIDIA introduces cuda.cccl, bridging the gap for Python developers by providing essential building blocks for CUDA kernel fusion, enhancing performance across GPU architectures. NVIDIA has unveiled a ...
Abstract: Accurate time series forecasting is crucial for optimizing resource allocation, industrial production, and urban management, particularly with the growth of cyber-physical and IoT systems.
Introduction: To provide better access to hearing aids and lower the devices' costs for patients with mild to moderate hearing loss, the Food and Drug Administration (FDA) changed its rules for ...
I am writing a kernel function where one of the parameters is a list. I have to annotate it, otherwise SK builds invalid metadata. Even after annotating the argument, the items in the list remain ...
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