Loss functions and constraints improve sea surface height prediction

In order to understand currents, tides and other ocean dynamics, scientists need to accurately capture sea surface height, or ...
EurekAlert!

AI-powered ECG analysis offers promising path for early detection of chronic obstructive pulmonary disease, says Mount Sinai researchers

Mount Sinai analysis looks at the effectiveness of electrocardiograms analyzed via deep learning as a tool for early COPD detection ...
AlphaGalileo

Adapting to the Stream: An Instance-Attention GNN Method for Irregular Multivariate Time Series Data

DynIMTS replaces static graphs with instance-attention that updates edge weights on the fly, delivering SOTA imputation and P12 classification ...

WiMi Releases Next-Generation Quantum Convolutional Neural Network Technology for Multi-Channel Supervised Learning

Beijing, Jan. 05, 2026 (GLOBE NEWSWIRE) -- WiMi Releases Next-Generation Quantum Convolutional Neural Network Technology for Multi-Channel Supervised Learning ...

MicroCloud Hologram stock rises after unveiling quantum spectral filter tech

MicroCloud Hologram’s approach uses a logarithmic encoding method to reduce the number of qubits needed, representing an N-dimensional feature space using just log (N) qubits. The system forms an ...
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 ...
IEEE

Global-Local Collaborative Graph Convolutional Network for Skeleton-Based Action Recognition

Abstract: Skeleton-based action recognition has emerged as a critical challenge in computer vision. In this task, local and global features describe actions from the perspectives of fine-grained ...
IEEE

MCGC-Net: Multi-scale Controllable Graph Convolutional Network on Music Emotion Recognition

Abstract: This paper introduces a novel dynamic graph learning approach for frequency graphs, underpinned by a suite of baseline methodologies and the Multi-scale Controllable Graph Convolutional ...