Nature

Transfer learning with graph neural networks for improved molecular property prediction in the multi-fidelity setting

We investigate the potential of graph neural networks (GNNs) for transfer learning and improved molecular property prediction in the context of funnels or screening cascades characteristic of drug ...
Nature

Supervised learning in DNA neural networks

Learning is a fundamental process driving adaptability and survival across biological scales. At the organismal level, neural rewiring and synaptic plasticity enable the brain to learn and form ...
Science Daily

Hidden geometry of learning: Neural networks think alike

Engineers have uncovered an unexpected pattern in how neural networks -- the systems leading today's AI revolution -- learn, suggesting an answer to one of the most important unanswered questions in ...

In 1986, three scientists improved backpropagation, making neural networks learn effectively from data

A groundbreaking 1986 technique called backpropagation revolutionized artificial intelligence, enabling computers to learn ...
The Manila Times

WiMi Develops Quantum Convolutional Neural Network Model for Classical Data Classification

WiMi Hologram Cloud Inc. (NASDAQ: WIMI) ('WIMI' or the 'Company'), a leading global Hologram Augmented Reality ('AR') Technology provider, has completed systematic benchmark testing on fully ...
Tech Xplore

Brain-inspired AI architecture could compute faster while using far less power

Spiking neural networks (SNNs) are artificial intelligence (AI) models inspired by how biological neurons communicate with ...
Phys.org

Self-learning neural network cracks iconic black holes

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 the ...
InfoWorld

The most popular neural network styles and how they work

Learn about the most prominent types of modern neural networks such as feedforward, recurrent, convolutional, and transformer networks, and their use cases in modern AI. Neural networks are the ...
Medical Xpress

Predicting 'sleep learning': Neural activity patterns reveal conditions for strengthening synaptic connections

In the cerebral cortex, numerous neurons exchange information through junctions known as synapses. The strength of each synaptic connection changes depending on the activity levels of the neurons ...
Tech Xplore on MSN

Forgetting may be the secret to better AI language learning

Giving AI a human-like memory limitation may actually help it learn language better. In their new proof-of-principle study, ...
Aerospace and Mechanical Insider on MSN

AI and machine learning transform materials testing

Materials testing remains a cornerstone of engineering and manufacturing, ensuring that components and structures—from ...
EurekAlert!

The hidden geometry of learning: neural networks think alike

Penn Engineers have uncovered an unexpected pattern in how neural networks — the systems leading today’s AI revolution — learn, suggesting an answer to one of the most important unanswered questions ...