From a neuroscience perspective, artificial neural networks are regarded as abstract models of biological neurons, yet they rely on biologically implausible backpropagation for training. Energy-based ...

Abstract: To improve the estimation accuracy of the state of charge (SOC) in power batteries for electric vehicles, this study proposes a novel modeling and online SOC estimation method using Back ...

Build your own backpropagation algorithm from scratch using Python — perfect for hands-on learners! Parkinson’s Isn’t Just Bad Luck. Scientists Reveal It’s Largely Preventable—and the Culprit Is All ...

This study aims to enhance the spatial resolution and accuracy of bathymetric prediction by integrating Gravity Anomaly (GA) and Vertical Gravity Gradient Anomaly (VGG) data with a dual-channel ...

Here’s a common scenario in companies around the world: The annual review of proposed new projects is coming up, and you’re on the decision-making committee. You and your colleagues are faced with an ...

A big part of AI and Deep Learning these days is the tuning/optimizing of the algorithms for speed and accuracy. Much of today’s deep learning algorithms involve the use of the gradient descent ...