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

WiMi Releases Next-Generation Quantum Convolutional Neural Network Technology for Multi-Channel Supervised Learning BEIJING, Jan. 05, 2026––WiMi Hologram Cloud Inc. (NASDAQ: WiMi) ("WiMi" or the ...
IEEE

GTAE-IDS: Graph Transformer-Based Autoencoder Framework for Real-Time Network Intrusion Detection

Abstract: Network intrusion detection systems (NIDS) utilize signature and anomaly-based methods to detect malicious activities within networks. Advances in machine learning (ML) and deep learning (DL ...
EurekAlert!

Development of an AI device using ion gel and graphene that dramatically streamlines machine learning computations

A joint research team from NIMS, Tokyo University of Science, and Kobe University has developed a new artificial intelligence ...
IEEE

Dynamic Graph-Based Deep Reinforcement Learning to V2X Channel Congestion Collaborative Control

Abstract: As an important component of intelligent transportation systems, vehicle-to-everything (V2X) provides critical communication support for road safety through real-time interactive and ...
C&EN

Integrating ESM-2 and Graph Neural Networks with AlphaFold-2 Structures for Enhanced Protein Function Prediction

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. Protein function prediction is essential for elucidating biological processes and ...
Sports Illustrated

Raiders Training Camp Report No. 14: Deep Dive on the New Depth Chart

Our latest episode of the Las Vegas Raiders Insider Podcast offers a deep dive look at today's practice and the latest Silver and Black depth chart. HENDERSON, Nev.—The Las Vegas Raiders moved indoors ...
Frontiers

Deep learning-based object detection for environmental monitoring using big data

Introduction: Recent advances in artificial intelligence have transformed the way we analyze complex environmental data. However, high-dimensionality, spatiotemporal variability, and heterogeneous ...
Frontiers

Cyclic peptide membrane permeability prediction using deep learning model based on molecular attention transformer

Membrane permeability is a critical bottleneck in the development of cyclic peptide drugs. Experimental membrane permeability testing is costly, and precise in silico prediction tools are scarce. In ...