The Lancet

Adaptive deep brain stimulation in Parkinson's disease

With the introduction of adaptive deep brain stimulation (aDBS) for Parkinson's disease, new questions emerge regarding who, why, and how to treat. This paper outlines the pathophysiological rationale ...
Hosted on MSN

Activation functions in neural networks: Types and examples

In this video, we will see What is Activation Function in Neural network, types of Activation function in Neural Network, why to use an Activation Function and which Activation function to use. The ...
Semiconductor Engineering

A Hybrid Subsystem Architecture To Elevate Edge AI

The world of artificial intelligence is moving beyond the cloud and into our everyday devices from smart sensors to robotics and AR/VR headsets. One of the key components that enables this shift is a ...
C&EN

Generation of Novel Fuels Optimized for High-Knock Resistance with a Long Short-Term Memory Model

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. The chemical structure of fuels significantly influences the properties of ignition ...
IEEE

ASTRA: Reconfigurable Training Architecture Design for Nonlinear Softmax and Activation Functions in Transformers

Abstract: The efficient training of Transformer-based neural networks on resource-constrained personal devices is attracting continuous attention due to domain adaptions and privacy concerns. However, ...
GitHub

[ENH] Better activation function for CNN multiclass classification

Softmax ensures the sum of all output probabilities is 1, making it ideal for multi-class classification, whereas Sigmoid treats each class independently, leading to probabilities that don’t sum to 1.