Neural network optimisation has emerged as a transformative approach in microwave engineering, driving enhancements in both the accuracy and speed of electromagnetic (EM) simulations and circuit ...

Explore how neuromorphic chips and brain-inspired computing bring low-power, efficient intelligence to edge AI, robotics, and ...

Neural network pruning is a key technique for deploying artificial intelligence (AI) models based on deep neural networks (DNNs) on resource-constrained platforms, such as mobile devices. However, ...

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 ...

This study presents SynaptoGen, a differentiable extension of connectome models that links gene expression, protein-protein interaction probabilities, synaptic multiplicity, and synaptic weights, and ...

Artificial intelligence has grown so large and power hungry that even cutting edge data centers strain to keep up, yet a technique borrowed from quantum physics is starting to carve these systems down ...

AI methods are increasingly being used to improve grid reliability. Physics-informed neural networks are highlighted as a ...

Even networks long considered "untrainable" can learn effectively with a bit of a helping hand. Researchers at MIT's Computer ...

Red Hat, the IBM-owned open source software firm, is acquiring Neural Magic, a startup that optimizes AI models to run faster on commodity processors and GPUs. The terms of the deal weren’t disclosed.

MicroCloud Hologram Inc. (NASDAQ: HOLO), ("HOLO" or the "Company"), a technology service provider, innovatively launches a quantum-enhanced deep convolutional neural network image 3D reconstruction ...

A research team led by Chang Keke from the Ningbo Institute of Materials Technology and Engineering (NIMTE), Chinese Academy of Sciences (CAS), has ...