We present a live performance for experimental electronic music in which a continuously evolving neural network joins two human performers to form an improvising trio. Rather than training a generative model on pre-existing works, we use neuroevolution strategies to grow a feed-forward neural graph in real time, with n...
Fabian Ostermann, Tim Löhde· Zenodo (CERN European Organi...· 0 citations
The increasing popularity of electric vehicles is inevitable due to their lower dependence on conventional fuel and reduced air pollution. Among various drivetrain architectures, four-wheel independently driven electric vehicles (4WID-EVs) have gained significant attention owing to their superior load-carrying and dyna...
This repository contains the dataset, source codes, trained graph models, and experimental outputs used in the research article entitled: "Resilient Real-Time Metro Rerouting with Adaptive Bidirectional Heuristics and Graph Neural Network-Based Edge Prediction" The provided materials support the implementation and eval...
An autonomous controller can act only on the state it can see, and in a compact spherical tokamak the state must be produced faster than the plant evolves, from a diagnostic set that survives a 14 neutron field and keeps working when individual channels drop out. We formalise the Hyperion breeder diagnostic suite — mag...
An autonomous controller can act only on the state it can see, and in a compact spherical tokamak the state must be produced faster than the plant evolves, from a diagnostic set that survives a 14 neutron field and keeps working when individual channels drop out. We formalise the Hyperion breeder diagnostic suite — mag...
The RatKpContext Benchmark (RKpC Benchmark) is the data companion to the manuscript “Dissecting Tissue-Context Effects in Graph Neural Networks for Rat Kp Prediction: Additive Shifts, Fusion Position, and Extrapolation.” It contains aggregate evaluation outputs for four graph neural network architectures under repeated...
Seonghan Kim, HyunSeo Cho, Hyeoncheol Jeong et al.· Zenodo (CERN European Organi...· 0 citations
From idea generation to testing, drug discovery is a lengthy and expensive process. Rather than chasing all of their molecule ideas, scientists prioritize certain molecules that are more likely to be successful, from synthesis to safety to therapeutic use. Machine learning and AI enable researchers to narrow their cand...
Dr. Pradyumna Kumar Pradhan· ChemRxiv· 0 citations
Gas turbines and their foundations and structural support systems operate as dynamically coupled thermo-mechanical assets whose degradation is governed by interacting aerodynamic, thermal, rotational, vibration, fatigue, settlement, stiffness-loss, and load-transfer mechanisms. Conventional condition-monitoring and rem...
Ransben Zac Addy, Aondoseer Abraham Atoo, Emmanuel Okechukwu Nwafor· Zenodo (CERN European Organi...· 0 citations
The efficiency and accuracy of existing student performance prediction technologies are low. This study proposes a prediction model that combines the Louvain algorithm and a hybrid neural network model. The model aims to improve the accuracy and efficiency of student performance prediction. The model uses graph folding...
Hequn Yang· International Journal of Com...· 0 citations
The new MACBDN approach is highly successful in integrating federated learning, graph representations, and the attention mechanism to maintain an optimal balance between the three parameters, and its lightweight nature and privacy-preserved design help it stay flexible for practical clinical settings and multi-party ho...
Asha Latha Thandu, Pradeepini Gera· The European Physical Journa...· 0 citations
Protein function annotation by propagating protein language model embeddings over protein-protein interaction networks, across the full range from parameter-free multi-hop diffusion to learned graph neural networks (GCN, GAT, GraphSAGE) and their fusion. This release is the archived snapshot of the code and derived res...
Yeonatan Mauhnoom, Gabriel Bianchin de Oliveira, Hélio Pedrini et al.· Zenodo (CERN European Organi...· 0 citations
Machine-learning networks can learn without detailed instructions from a designer. Those that do may offer insight into how the brain reorganizes itself during learning.
MIT News · Artificial Intelligence· news.mit.eduJul 15, 2026
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.