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ABSTRACT: This paper deals with three traditional measures of concentration: (Corrado) Gini coefficient, adjusted Gini coefficient, and AUC. These metrics are popular methods in assessing the ...

Faculty of Chemistry, Institute of Computational Biological Chemistry, University of Vienna, Wien 1090, Austria Vienna Doctoral School of Chemistry (DosChem), University of Vienna, Wien 1090, Austria ...

Abstract: We created a scatterer database based on the modified MNIST data set. Using simple neural networks, we achieve a 90% accuracy in classifying objects. We investigated the accuracy as a ...

We will create a Deep Neural Network python from scratch. We are not going to use Tensorflow or any built-in model to write the code, but it's entirely from scratch in python. We will code Deep Neural ...

Introduction: Accurate vehicle analysis from aerial imagery has become increasingly vital for emerging technologies and public service applications such as intelligent traffic management, urban ...

A new study led by researchers from the Yunnan Observatories of the Chinese Academy of Sciences has developed a neural network-based method for large-scale celestial object classification, according ...

Background: Biomarker discovery and drug response prediction are central to personalized medicine, driving demand for predictive models that also offer biological insights. Biologically informed ...

This tutorial will walk you through using PyTorch to implement a Neural Collaborative Filtering (NCF) recommendation system. NCF extends traditional matrix factorisation by using neural networks to ...