Current methods generate these mappings from interpolation using a few sparse data points recorded inside the atria; they neither include prior knowledge of the underlying physics nor uncertainty of ...

In this paper, a novel fusion method on the multimodal medical images exploiting convolutional neural network (CNN) and extreme learning machine (ELM ... Step 1.1: The patch of 32 × 32 pixels are fed ...

config_frequentist.py: Hyperparameters for main_frequentist file. @article{shridhar2019comprehensive, title={A comprehensive guide to bayesian convolutional neural network with variational inference}, ...

Network models are a computer architecture, implementable in either hardware or software, meant to simulate biological populations of interconnected neurons. These models, also known as ...

To help identify core network requirements and shape the future networks’ design paradigm, this Technical Report summarizes some representative use cases for Network 2030. Part I presents the ...

We used administrative Medicare enrollment and traditional Medicare claims data to identify 2018 enrollees of discontinued plans, their out-of-network utilization in 2018, and their subsequent ...

with respect to the Network 2030 services, capabilities, and representative use cases. Based on these inputs, the report identifies gaps, namely issues and technologies that are not currently ...

Abstract: Software-defined networks (SDNs) have fundamentally transformed the networking industry over the past decade, giving network operators unprecedented flexibility to customize network behavior ...