A critical procedure in diagnosing atrial fibrillation is the creation of electro-anatomic activation maps. Current methods generate these mappings from interpolation using a few sparse data points ...

Spiking Neural Networks (SNNs) are a pathway that could potentially empower low-power event-driven neuromorphic hardware due to their spatio-temporal information ...

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

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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 ...

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Traditional approaches to training language models heavily rely on supervised fine-tuning, where models learn by imitating correct responses. While effective for basic tasks, this method limits a ...