Allison DeAngelis is the East Coast biotech and venture capital reporter at STAT, reporting where scientific ideas and money meet. She is also co-host of the weekly biotech podcast, The Readout Loud.

Abstract: Radial basis function neural networks (RBFNNs) have been widely used in data modeling and prediction in recent years. However, an RBFNN does not perform well when it comes to practical ...

Implement Neural Network in Python from Scratch ! In this video, we will implement MultClass Classification with Softmax by making a Neural Network in Python from Scratch. We will not use any build in ...

Confused about activation functions in neural networks? This video breaks down what they are, why they matter, and the most common types — including ReLU, Sigmoid, Tanh, and more! #NeuralNetworks ...

ABSTRACT: This paper presents the mathematical models and calculation of states of matter dynamics (gasses, fluids, solids) and phase transitions from statistical viewpoint, with new calculation ...

Abstract: The radial basis function neural network (RBFNN) is a learning model with better generalization ability, which attracts much attention in nonlinear system identification. Compared with the ...

Cucumber cultivation faces two pressing challenges: balancing shoot architecture with drought tolerance. New research has uncovered that the CsTIE1–CsAGL16 module serves as a pivotal regulator in ...

Hi, thank you for this great package! I was wondering whether it would be straightforward to combine this package with Lux.jl to build a radial basis function network (RBFN). Has anyone tried that?

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ABSTRACT: We solve numerically an eigenvalue elliptic partial differential equation (PDE) ranging from two to six dimensions using the generalized multiquadric (GMQ) radial basis functions (RBFs). Two ...