ORIGO/MD-V: A Dimensionless Topological Structure Class for Universal Coupling of Dynamical Systems (Patent, Hardware Validation, Simulation). ORIGO/MD-V is a dimensionless, topological, decentralized structure class for describing dynamical systems without the artefacts c (speed of light), t (time), and G (gravitation...
Markus Drößler· Zenodo (CERN European Organi...· 0 citations
Anorthite-NAD is a molecular-dynamics dataset for studying learned nonequilibrium atomistic dynamics under controlled deformation. It contains 36 independent LAMMPS trajectories and 18,000 graph-state transitions of crystalline anorthite (CaAl₂Si₂O₈) at 300 K, spanning isotropic and axis-specific deformation at final s...
Nayan Naleyanda· Zenodo (CERN European Organi...· 0 citations
Real-time quantum error correction for superconducting processors requires decoding streaming syndrome data within microsecond cycle intervals (T_cycle ≈ 1.1 μs). Classical minimum-weight perfect matching executed on host processors suffers from communication and serial matching bottlenecks, creating an exponential dec...
ORIGO/MD-V: A Dimensionless Topological Structure Class for Universal Coupling of Dynamical Systems (Patent, Hardware Validation, Simulation). ORIGO/MD-V is a dimensionless, topological, decentralized structure class for describing dynamical systems without the artefacts c (speed of light), t (time), and G (gravitation...
Markus Drößler· Zenodo (CERN European Organi...· 0 citations
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This dataset contains structural molecular property indices (SMPI) calculated for a benchmark collection of 33,715 organic molecules. The dataset is provided as a tab-separated text file (smpi-nog33715mols2.txt) designed for chemoinformatics analysis, quantitative structure-activity/property relationship (QSAR/QSPR) mo...
Lorentz Jäntschi, Alexandra Farcaș· Zenodo (CERN European Organi...· 0 citations
Manufacturing inspection combines measurements taken on irregular geometries with decisions about conformity, rework, and further examination. Graph neural networks can represent these measurements, but geometric connectivity, physical consistency, and defect evidence are different forms of information. This review dev...
Based on the GFUM v4.1 neural fluid network framework, this study applies formallogic mathematical induction to execute a proof of exhaustive exclusion and extremequantitative testing regarding the global regularity of the Navier-Stokes (N-S) equations—aMillennium Prize Problem. We construct a complete graph topologica...
华建 戚· Zenodo (CERN European Organi...· 0 citations
Abstract Human activity recognition is essential for supporting independent living. Although image-based approaches have achieved significant progress, they raise privacy concerns, and require adequate and stable lighting conditions. Millimetre-wave (mmWave) radar provides a privacy-preserving alternative; however, its...
Vincent Gbouna Zakka, Luis J. Manso, Zhuangzhuang Dai· Journal of Ambient Intellige...· 0 citations
Existing coke quality prediction methods mainly rely on a two-stage prediction strategy, where blended coal properties are first estimated from individual coal properties and then used for coke quality prediction. This process inevitably introduces information loss and accumulated prediction errors, which limit the pre...
This paper introduces a unified, three-layer converged security architecture designed to shield critical digital infrastructure from both classical cyber threats and emerging quantum decryption risks. The architecture integrates a DNA-steganography post-quantum key exchange scheme to secure inter-layer communications,...
A graph neural network (GNN)‐based framework for scalable multiagent reinforcement learning (RL), where each manipulator is represented as a node in a GNN, and message‐passing edges provide a communication mechanism that enables agents to share information effectively.
Tong Chen, Bo Fu, Dawn M. Tilbury et al.· Advanced Intelligent Systems· 0 citations
This version corrects one citation error found by an automated check and confirmed by hand: a paper on self-regulatory communication in evolved neural agents, listed among those considered and not included, was cited under the identifier 2602.02840, which belongs to an unrelated paper; the correct identifier is arXiv:2...
Saluca Agentic AI Research Team· Zenodo (CERN European Organi...· 0 citations
Assistant Professor Pat Pataranutaporn describes a new interface that lets everyday users glimpse inside an AI's neural network before their chatbot ever says a word.
Microsoft Research Blog· microsoft.comJul 13, 2026
Cryptographic code supports vital protections in modern computing systems. Learn how a new method helps verify code as developers write it while preserving speed and adaptability as it gets implemented and evolves. The post Verifying Rust cryptography in SymCrypt, from standards to code appeared first on Microsoft Research.
MIT News · Artificial Intelligence· news.mit.eduJul 6, 2026
PhD student Rachel Sava, winner of the Envisioning the Future of Computing Prize, explores transformative improvements and dystopian risks of neural technology.
