As for the AI bubble, it is coming up for conversation because it is now having a material effect on the economy at large.

State Key Laboratory of Precision Measuring Technology and Instruments, Tianjin University, Tianjin 300072, China ...

The fund-raising round comes as online prediction marketplaces gain mainstream prominence. By Michael J. de la Merced Online prediction markets have jumped into the mainstream, as users flock to sites ...

Learn how to build a fully connected, feedforward deep neural network from scratch in Python! This tutorial covers the theory, forward propagation, backpropagation, and coding step by step for a hands ...

Abstract: The Graph Neural Network (GNN) methods based on enclosing subgraph extraction have achieved excellent results in static graph link prediction tasks. However, most real-world networks are ...

STM-Graph is a Python framework for analyzing spatial-temporal urban data and doing predictions using Graph Neural Networks. It provides a complete end-to-end pipeline from raw event data to trained ...

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 ...

The Supporting Information is available free of charge at https://pubs.acs.org/doi/10.1021/acs.jcim.5c01525. Efficiency analysis of different normalization strategies ...

Please be aware that this is a beta release. Beta means that the product may not be functionally or feature complete. At this early phase the product is not yet expected to fully meet the quality, ...

Artificial neural networks are machine learning models that have been applied to various genomic problems, with the ability to learn non-linear relationships and model high-dimensional data. These ...