Will AI‑Driven Modeling Breakthrough in Semiconductor Design Change Keysight Technologies' (KEYS) Narrative?

Keysight Technologies has recently launched a new Machine Learning Toolkit within its Device Modeling Software Suite, using ...
TMCnet

MicroCloud Hologram Inc. Releases Learnable Quantum Spectral Filter Technology for Hybrid Graph Neural Networks

MicroCloud Hologram Inc. (NASDAQ: HOLO), ("HOLO" or the "Company"), a technology service provider, released learnable quantum spectral filter technology for hybrid graph neural networks. This ...
Ars Technica

Researchers isolate memorization from problem-solving in AI neural networks

When engineers build AI language models like GPT-5 from training data, at least two major processing features emerge: memorization (reciting exact text they’ve seen before, like famous quotes or ...
GitHub

What are neural networks?

What is a neural network? A neural network, also known as an artificial neural network, is a type of machine learning that works similarly to how the human brain processes information. Instead of ...
C&EN

A Multilinear Regression Procedure for Solving the Inverse Problem with Physics-Informed Neural Networks: Application to Three Case Studies in Chemical Engineering

Department of Mechanical, Chemical and Materials Engineering, University of Cagliari, Piazza d’Armi, 09123 Cagliari, Italy ...
Frontiers

Neural-enhanced motion-to-EMG: refining simulated muscle activity from musculoskeletal models using a Seq2Seq approach

Electromyography (EMG) is essential for accurate assessment of motor function in rehabilitation, sports science, and robotics. However, its various time-consuming human operations (e.g., ...
IEEE

Optimization Over Trained Neural Networks: Difference-of-Convex Algorithm and Application to Data Center Scheduling

Abstract: When solving decision-making problems with mathematical optimization, some constraints or objectives may lack analytic expressions but can be approximated from the data. When an ...