NEURON has been widely used as an empirically-based simulation tool, especially for multi-compartment conductance-based neuronal modeling. The network mediating feeding in Aplysia californica has been ...

Neural networks constitute a well-established and extensively studied area of modern computational technology. Among available frameworks, TensorFlow remains one of the most prevalent platforms for ...

If you have trouble following the instruction below, feel free to join OSCER weekly zoom help sessions. If you're doing deep learning neural network research, tensorflow need no introduction. It is ...

ABSTRACT: Background: The diagnosis and follow-up of mental disorders still rely heavily on subjective clinical assessments, highlighting the need for objective and quantitative monitoring methods.

Abstract: We propose a user-friendly neural network framework on the open-source TensorFlow platform to analyze and mitigate power amplifier distortion. Using simulation data of a 2 W GaN power ...

This paper proposes a B-spline neural operator for real-time CPS safety, combining neural networks with inductive bias to predict system behavior on a quadrotor. Control systems are critical in ...

A distinguishing feature of the neural network models used in Physics and Chemistry is that they must obey basic underlying symmetries, such as symmetry to translations, rotations, and the exchange of ...

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