How do AI coding agents work? We look under the hood.

At the core of every AI coding agent is a technology called a large language model (LLM), which is a type of neural network ...

Kolmogorov-Arnold networks bridge AI and scientific discovery by increasing interpretability

AI has successfully been applied in many areas of science, advancing technologies like weather prediction and protein folding ...

Open-source software sheds light on cancer's hidden genetic networks

University of Navarra (Spain) researchers have developed RNACOREX, a new open-source software capable of identifying gene ...
eLife

High-Fidelity Neural Speech Reconstruction through an Efficient Acoustic-Linguistic Dual-Pathway Framework

This study presents a valuable advance in reconstructing naturalistic speech from intracranial ECoG data using a dual-pathway model. The evidence supporting the claims of the authors is solid, ...
EurekAlert!

New multi-modal AI framework brings human-like reasoning to self-driving vehicles

Autonomous driving systems increasingly rely on data-driven approaches, yet many still struggle with reasoning, handling rare scenarios, and transparently explaining their actions. A new study ...
IEEE

Autoencoder-Enhanced Ensemble Neural Network for Forced Oscillation Source Location in Renewable-Rich Power Systems

Abstract: Conventional energy-based methods struggle to determine the origin of Forced Oscillations (FOs) in renewable-rich systems because of their dependency on Dissipating Energy Flow (DEF) ...
T&D

Sandia National Laboratories’ Research Team Develop AI Algorithms to Detect Physical Issues, Cyberattacks within Grid

Researchers at Sandia National Laboratories have developed AI algorithms to detect physical problems, cyberattacks and both at the same time within the grid. “As more disturbances occur, whether from ...
IEEE

Autoencoder-Augmented Graph Neural Networks for Accurate and Scalable Structure Recognition in Analog/Mixed-Signal Schematics

Abstract: The increasing complexity of Analog/Mixed-Signal (AMS) schematics has been posing significant challenges in structure recognition, particularly in the intellectual property (IP) industry, ...
INSPIRE

Quantum Error Mitigation via Autoencoder Neural Networks

Quantum computing has gained significant attention in recent years, with numerous algorithms and applications under active development. Limited by the current quantum ...
GitHub

The autoencoder performs very poorly

Thank you very much for your outstanding work. Recently, I came across your research results and was immediately intrigued. I attempted to train a parameter autoencoder using my own set of parameters, ...