Introduction Asthma is a chronic respiratory disorder requiring ongoing medical management. This ecological study investigated the spatial and temporal patterns of notification rates for asthma from ...
Deep learning uses multi-layered neural networks that learn from data through predictions, error correction and parameter adjustments. It started with the ...
Meta released details about its Generative Ads Model (GEM), a foundation model designed to improve ads recommendation across ...
This study presents a valuable advance in reconstructing naturalistic speech from intracranial ECoG data using a dual-pathway model. The evidence supporting the claims of the authors is solid, ...
Variable names are alphanumeric but must start with a letter. The length of a variable name is limited to thirty-two characters for non-SAS data set variables Model variables are declared by VAR, ...
Abstract: Thanks to the development of deep learning, machine abnormal sound detection (MASD) based on unsupervised learning has exhibited excellent performance. However, in the task of unsupervised ...
KernelOptimizer is an open-source tool that automates CUDA kernel optimization for PyTorch workloads using large language models (LLMs). Inspired by Stanford CRFM’s fast kernel research, it leverages ...
Abstract: Although deep learning-based surface defect detection approaches have performed remarkably well in recent years, the complicated shapes and large size differences of surface defects still ...
MB_DEVICE_ADDR1 CID_INP_DATA_0, Data_channel_0 Data channel 1 MB_DEVICE_ADDR1 CID_HOLD_DATA_0, Humidity_1 Humidity 1 MB_DEVICE_ADDR1 CID_INP_DATA_1 Temperature_1 ...
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