Art of the Problem on MSNOpinion

The second computing revolution, why neural networks replaced 70 years of human-written rules

For decades, computers did exactly what humans told them, until a biologically inspired idea quietly made that approach ...
Nature

Deep Reinforcement Learning for Resource Management in Wireless Networks

Deep reinforcement learning has emerged as a powerful model-free framework for managing scarce wireless resources under highly dynamic conditions. By casting tasks such as spectrum allocation, power ...
Phys.org

Using geometry and physics to explain feature learning in deep neural networks

Deep neural networks (DNNs), the machine learning algorithms underpinning the functioning of large language models (LLMs) and other artificial intelligence (AI) models, learn to make accurate ...
Phys.org

Q&A: How mathematics can reveal the depth of deep learning AI

Artificial intelligence (AI) is increasingly prevalent, integrated into phone apps, search engines and social media platforms as well as supporting myriad research applications. Of particular interest ...
EurekAlert!

Deep neural networks enable accurate pricing of American options under stochastic volatility

It shows the schematic of the physics-informed neural network algorithm for pricing European options under the Heston model. The market price of risk is taken to be λ=0. Automatic differentiation is ...
JSTOR Daily

Automated and accurate segmentation of leaf venation networks via deep learning

• Leaf vein network geometry can predict levels of resource transport, defence and mechanical support that operate at different spatial scales. However, it is challenging to quantify network ...
Neuroscience News

AI Model Predicts Complex DNA Binding

Researchers develop BINND, a deep learning model that predicts complex DNA-DNA binding with 83.5% accuracy, unlocking scalable DNA computing.