Abstract: Neuro-transfer function (Neuro-TF) has emerged as a prominent approach for electromagnetic (EM) parametric modeling, though traditional implementations for TF parameter extraction relying on ...

This is a pytorch implementation of the Muti-task Learning using CNN + AutoEncoder. Cifar10 is available for the datas et by default. You can also use your own dataset. epoch,train loss,train accuracy ...

Graph Convolutional Networks (GCNs) are widely applied for spatial domain identification in spatial transcriptomics (ST), where node representations are learned by aggregating information from ...

ABSTRACT: This work focuses on the security of mobile payments in Internet of Things networks, with particular emphasis on the integration of post-quantum cryptographic principles. The study adopts a ...

ABSTRACT: With the deepening of oil and gas exploration, the exploration targets have gradually shifted from structural oil and gas reservoirs to lithological oil and gas reservoirs. The fluvial ...

Google has reportedly initiated the TorchTPU project to enhance support for the PyTorch machine learning framework on its tensor processing units (TPUs), aiming to challenge the software dominance of ...

Point of care ultrasound (POCUS) is commonly used for diagnostic triage of internal injuries in both civilian and military trauma. In resource constrained environments, such as mass-casualty ...

SVG Autoencoder - Uses a frozen representation encoder with a residual branch to compensate the information loss and a learned convolutional decoder to transfer the SVG latent space to pixel space.