One significant advancement in this field is the introduction of PDE-based G-CNNs, which generalize traditional convolutional neural networks by incorporating partial differential equations (PDEs ...

The day has come: the RTX 50-series has arrived and we're here to share exactly what you can expect from its flagship. This ...

Neural networks have revolutionized the fields of artificial intelligence (AI) and machine learning by providing a flexible, ...

Engineering simulations often require significant computational resources and time, which creates barriers for users and can ...

Learn More A new neural-network architecture developed by researchers at Google might solve one of the great challenges for large language models (LLMs): extending their memory at inference time ...

and Random Forest Classifier and three widely used deep learning algorithms – Deep Neural Network, Convolutional Neural Network and Recurrent Neural Network were trained and tested on the dataset on ...

A Fortran-based feed-forward neural network library. Whilst this library currently has a focus on 3D convolutional neural networks (CNNs), it can handle most standard hidden layer forms of neural ...

In the context of power generation companies, vast amounts of specialized data and expert knowledge have been accumulated. However, challenges such as data silos and fragmented knowledge hinder the ...

An Image Recognition Model That uses a Convolution Neural Network with Tensorflow to be able to tell an animal from a non-animal image ...