Results 201 to 210 of about 427,529 (281)
Data‐Driven Review and Machine Learning Prediction of Diamond Vacancy Center Synthesis
A machine learning framework is applied to photoluminescence spectra to extract linewidths and uncover how NV, SiV, GeV, and SnV centers evolve with growth and processing conditions. Unified normalization and k‐fold validation reveal cross‐method trends and enable rapid prediction of defect size and fabrication parameters, offering a data‐driven route ...
Zhi Jiang +3 more
wiley +1 more source
Temporal succession and assembly of marine bacterial communities in Maxwell Bay, Antarctica during summer. [PDF]
Zeng H +9 more
europepmc +1 more source
Terrestrial Cyborg Insects for Real‐Life Applications
This article reviews the development of terrestrial cyborg insects from their emergence in 1997 to mid‐2025, examining three key aspects: locomotion control methods, associated challenges with proposed solutions, and practical applications. Framing these biohybrid systems as insect‐scale mobile robots, the review provides foundational insights for new ...
Hai Nhan Le +10 more
wiley +1 more source
Learning in Probabilistic Boolean Networks via Structural Policy Gradients. [PDF]
Rivera Torres PJ.
europepmc +1 more source
Deep Reinforcement Learning Approaches for Sensor Data Collection by a Swarm of UAVs
This article presents four decentralized reinforcement learning algorithms for autonomous data harvesting and investigates how collaboration improves collection efficiency. It also presents strategies to minimize training times by improving model flexibility, enabling algorithms to operate with varying number of agents and sensors.
Thiago de Souza Lamenza +2 more
wiley +1 more source
TimesNet-BFT: Mitigating Network State Uncertainty in Byzantine Consensus via Deep Temporal Modeling. [PDF]
Wang H, Liu H, Liu Y, Ma H, Gao P.
europepmc +1 more source
This study provides an introduction to Bayesian optimisation targeted for experimentalists. It explains core concepts, surrogate modelling, and acquisition strategies, and addresses common real‐world challenges such as noise, constraints, mixed variables, scalability, and automation.
Chuan He +2 more
wiley +1 more source
Uncertainty Quantification for <i>In Silico</i> Chemistry. [PDF]
Frömbgen T +5 more
europepmc +1 more source
This review explores the transformative impact of artificial intelligence on multiscale modeling in materials research. It highlights advancements such as machine learning force fields and graph neural networks, which enhance predictive capabilities while reducing computational costs in various applications.
Artem Maevskiy +2 more
wiley +1 more source
Towards three-dimensional discrete fracture network modeling using integrated multidimensional outcrop data. [PDF]
Racolte G +6 more
europepmc +1 more source

