Deep neural networks are at the heart of artificial intelligence, ranging from pattern recognition to large language and ...

Adaptive Hierarchical Multi-Headed Convolutional Neural Network With Modified Convolutional Block Attention for Aerial Forest Fire Detection Abstract: Effective detection and classification of forest ...

A team of astronomers led by Michael Janssen (Radboud University, The Netherlands) has trained a neural network with millions of synthetic black hole data sets. Based on the network and data from ...

In 1982 physicist John Hopfield translated this theoretical neuroscience concept into the artificial intelligence realm, with the formulation of the Hopfield network. In doing so, not only did he ...

Energy and memory: A new neural network paradigm A dynamic energy landscape is at the heart of theorists' new model of memory retrieval Date: May 14, 2025 Source: University of California - Santa ...

Instead of applying the two-step algorithmic memory retrieval on the rather static energy landscape of the original Hopfield network model, the researchers describe a dynamic, input-driven mechanism.

While GCN and LSTM have achieved high prediction accuracy, few researchers have explored this approach in the context of MEG classification. To address the limitation of low accuracy in MEG multi-task ...

Titans architecture complements attention layers with neural memory modules that select bits of information worth saving in the long term.

The 2024 Nobel Prize in Physics has been awarded to scientists John Hopfield and Geoffrey Hinton “for foundational discoveries and inventions that enable machine learning with artificial neural ...