Recent research has employed chemical reaction networks (CRNs), which harness biochemical processes for computations that translate interactions involving biochemical species into graphical form.

A new study utilizes compact neural networks to uncover the underlying mechanisms behind human decision-making. Scientists have long studied how people and animals make decisions, often looking at how ...

By learning the relevant features of clinical images along with the relationships between them, the neural network can outperform more traditional methods.

Delve into the implications of AI in architecture: a tool that redefines creativity while risking the depth and intent behind design.

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 ...

Zhang, S., Fang, Y. and Ren, Y. (2024) ECG Autoencoder Based on Low-Rank Attention. Scientific Reports, 14, Article No. 12823.

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 ...

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 ...

The newly discovered dangers of RAG Here's what Bloomberg's AI researchers discovered: RAG can actually make models less "safe" and their outputs less reliable.

University of Virginia School of Engineering and Applied Science. (2024, October 24). New AI model could make power grids more reliable amid rising renewable energy use.