Package for the data-driven representation of non-linear dynamics over manifolds based on a statistical distribution of local phase portrait features. Includes specific example on dynamical systems, ...

Recently, a research team led by Prof. GAO Xiaoming from the Hefei Institutes of Physical Science of the Chinese Academy of Sciences, developed an intelligent neural network algorithm that effectively ...

ABSTRACT: The research focuses on improving predictive accuracy in the financial sector through the exploration of machine learning algorithms for stock price prediction. The research follows an ...

[IEEE TGRS 2020] Official Tensorflow implementation for Change Detection in Multisource VHR Images via Deep Siamese Convolutional Multiple-Layers Recurrent Neural Network ...

Neuromorphic computing, which is inspired by brain neural mechanisms and cognitive behavior mechanisms by means of computational modeling, is emerging with the promise of transforming information ...

Abstract: The purpose of this work is to improve the detection of fraud websites using Novel Linear Regression Algorithm and Recurrent Neural Network Algorithm. Materials and Methods: Novel Linear ...

Abstract: A new era of computational efficacy and problem-solving abilities has begun with the combination of Recurrent Neural Networks (RNNs) and computer science methods. It is crucial in modern ...

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. Spectroscopic methods─like nuclear magnetic resonance, mass spectrometry, X-ray ...

Department of Medicinal Chemistry, Research and Early Development, Respiratory and Immunology, Biopharmaceutical R&D, AstraZeneca, Pepparedsleden 1, SE 43183 Mölndal, Sweden ...