Abstract: Artificial neural networks (ANNs) rely significantly on activation functions for optimal performance. Traditional activation functions such as ReLU and Sigmoid are commonly used. However, ...

Introduction: Causal inference of athletic injuries provides the critical foundations for the development of effective prevention strategies. In recent years, the directed acyclic graph model (DAG) ...

The core of the Python data model architecture is special methods (also known as "magic methods"). These methods, which start and end with double underscores, such as __init__, __getitem__, and __len_ ...

The core of the Python data model architecture is the special methods (also known as 'magic methods'). These methods, which begin and end with double underscores, such as __init__, __getitem__, __len_ ...

The Furness method (1965), also known as Fratar method, holds a significant place in the domain of transportation planning, specifically in the crucial task of estimating trip generation within ...

Abstract: Mutual learning that can be seen as a derivative method of knowledge distillation takes advantages of the collective capabilities of multiple neural networks to promote the precision and ...

From the docs and the code here I can see that the usage of custom worker extensions is not longer supported in python 3.13. All of our function apps are heavily dependent on these extensions, making ...