Add to ORKGArtificial Neural Networks (ANNs) are complex modelling techniques that can be used to find the relation between the output of a complex multivariable function and its arguments, effectively approximating it
Machine learning has been a computer sciences buzzword for years. The technology has a lot of potent...
An approach to develop response surface approximations based upon artificial neural networks trained...
Machine learning is a technology developed for extracting predictive models from data so as to be ...
Artificial Neural Network (ANN) is one of the modern computational methods proposed to solve increas...
Artificial Neural Networks (ANNs) are complex modelling techniques that can be used to find the rela...
This is Chapter 3 of the book titled "Deep Learning": a nine-part easy-to-grasp textbook written wit...
Developments in deep learning with ANNs (Artificial Neural Networks) are paving the way for revoluti...
A biological neurone receives inputs from many sources, combines and presents them as a non-linear o...
This paper is a mathematical introduction to Artificial Neural Network (ANN). We will show how it is...
When used for function approximation purposes, neural networks belong to a class of models whose par...
Özyeğin University Technical ReportAn artificial neural network (ANN) is a computational model − imp...
Artificial Neural Networks are a Machine Learning algorithm based on the structure of biological neu...
This concise paper explains the inspiration of AI particularly artificial neural networks (ANNs) for...
The focus of this paper is on the neural network modelling approach that has gained increasing recog...
In the recent decade, deep neural networks have solved ever more complex tasks across many fronts in...
Machine learning has been a computer sciences buzzword for years. The technology has a lot of potent...
An approach to develop response surface approximations based upon artificial neural networks trained...
Machine learning is a technology developed for extracting predictive models from data so as to be ...
Artificial Neural Network (ANN) is one of the modern computational methods proposed to solve increas...
Artificial Neural Networks (ANNs) are complex modelling techniques that can be used to find the rela...
This is Chapter 3 of the book titled "Deep Learning": a nine-part easy-to-grasp textbook written wit...
Developments in deep learning with ANNs (Artificial Neural Networks) are paving the way for revoluti...
A biological neurone receives inputs from many sources, combines and presents them as a non-linear o...
This paper is a mathematical introduction to Artificial Neural Network (ANN). We will show how it is...
When used for function approximation purposes, neural networks belong to a class of models whose par...
Özyeğin University Technical ReportAn artificial neural network (ANN) is a computational model − imp...
Artificial Neural Networks are a Machine Learning algorithm based on the structure of biological neu...
This concise paper explains the inspiration of AI particularly artificial neural networks (ANNs) for...
The focus of this paper is on the neural network modelling approach that has gained increasing recog...
In the recent decade, deep neural networks have solved ever more complex tasks across many fronts in...
Machine learning has been a computer sciences buzzword for years. The technology has a lot of potent...
An approach to develop response surface approximations based upon artificial neural networks trained...
Machine learning is a technology developed for extracting predictive models from data so as to be ...