eLife

An interpretable neural network unveils higher-order epistasis in large protein sequence-function relationships

In this important work, the authors present a new transformer-based neural network designed to isolate and quantify higher-order epistasis in protein sequences. They provide solid evidence that higher ...
Hosted on MSN

20 activation functions in Python for deep neural networks – ELU, ReLU, Leaky-ReLU, Sigmoid, Cosine

Explore 20 different activation functions for deep neural networks, with Python examples including ELU, ReLU, Leaky-ReLU, Sigmoid, and more. #ActivationFunctions #DeepLearning #Python Teens arrested ...
Scientific Research Publishing

Vanishing Gradients in an Artificial Deep Neural Network: The Impact of Activation Functions and Optimization Techniques ()

Artificial deep neural networks (ADNNs) have become a cornerstone of modern machine learning, but they are not immune to challenges. One of the most significant problems plaguing ADNNs is the ...
Hosted on MSN

What Are Activation Functions in Deep Learning? Explained Clearly

Understand what activation functions are and why they’re essential in deep learning! This beginner-friendly explanation covers popular functions like ReLU, Sigmoid, and Tanh—showing how they help ...
Scientific Research Publishing

Asaad, R.R. and Ali, R.I. (2019) Back Propagation Neural Network (BPNN) and Sigmoid Activation Function in Multi-Layer Networks. Academic Journal of Nawroz University, 8, 216-221.

ABSTRACT: The accurate prediction of backbreak, a crucial parameter in mining operations, has a significant influence on safety and operational efficiency. The occurrence of this phenomenon is ...
IEEE

Skew Logistic Distribution Applied as Activation Function in Artificial Neural Networks

Abstract: In recent years, Artificial Neural Networks (ANNs) have stood out among machine learning algorithms in many applications, such as image and video pattern recognition. Activation functions ...
IEEE

Modeling of X-ray CT image by using revised GMDH-type neural networks with sigmoid functions

Abstract: In this paper, X-ray CT image is identified by using a revised GMDH-type neural network with sigmoid functions. The revised GMDH-type neural network algorithm with sigmoid functions proposed ...