Results 101 to 110 of about 212,052 (259)

Riemannian Geometry for the Classification of Brain States with Intracortical Brain Recordings

Advanced Intelligent Systems, EarlyView.
Geometric machine learning is applied to decode brain states from invasive intracortical neural recordings, extending Riemannian methods to the invasive regime where data is scarcer and less stationary. A Minimum Distance to Mean classifier on covariance manifolds uses geodesic distances to outperform convolutional neural networks while reducing ...
Arnau Marin‐Llobet, Sergio Sánchez‐Manso, Arnau Manasanch, Lluc Tresserras, Xinhe Zhang, Yining Hua, Hao Zhao, Melody Torao‐Angosto, Maria V Sanchez‐Vives, Leonardo Dalla Porta   +9 more
wiley   +1 more source

On the design and evaluation of generative models in high energy density physics

Communications Physics
Understanding high energy density physics (HEDP) is critical for advancements in fusion energy and astrophysics. The computational demands of the computer models used for HEDP studies have led researchers to explore deep learning methods to enhance ...
Ankita Shukla, Yamen Mubarka, Rushil Anirudh, Eugene Kur, Derek Mariscal, Blagoje Djordjevic, Bogdan Kustowski, Kelly Swanson, Brian Spears, Peer-Timo Bremer, Tammy Ma, Pavan Turaga, Jayaraman J. Thiagarajan   +12 more
doaj   +1 more source

BMPCQA: Bioinspired Metaverse Point Cloud Quality Assessment Based on Large Multimodal Models

Advanced Intelligent Systems, EarlyView.
This study presents a bioinspired metaverse point cloud quality assessment metric, which simulates the human visual evaluation process to perform the point cloud quality assessment task. It first extracts rendering projection video features, normal image features, and point cloud patch features, which are then fed into a large multimodal model to ...
Huiyu Duan, Kang Fu, Sijing Wu, Yunhao Li, Zicheng Zhang, Qiang Hu, Xiongkuo Min, Guangtao Zhai   +7 more
wiley   +1 more source

RPSLearner: A Novel Approach Based on Random Projection and Deep Stacking Learning for Categorizing Non‐Small Cell Lung Cancer

Advanced Intelligent Systems, EarlyView.
Identifying non‐small cell lung cancer (NSCLC) subtypes is essential for precision cancer treatment. Conventional methods are laborious, or time‐consuming. To address these concerns, RPSLearner is proposed, which combines random projection and stacking ensemble learning for accurate NSCLC subtyping. RPSLearner outperforms state‐of‐the‐art approaches in
Xinchao Wu, Jieqiong Wang, Shibiao Wan
wiley   +1 more source

Hierarchical Language Models for Semantic Navigation and Manipulation in an Aerial‐Ground Robotic System

Advanced Intelligent Systems, EarlyView.
A hierarchical multimodal framework coupling a large language model for task decomposition and semantic mapping with a fine‐tuned vision‐language model for semantic perception, enhanced by GridMask, is presented. An aerial‐ground robot team exploits the semantic map for global and local planning.
Haokun Liu, Zhaoqi Ma, Yunong Li, Junichiro Sugihara, Yicheng Chen, Jinjie Li, Moju Zhao   +6 more
wiley   +1 more source

Bridging High‐Fidelity Simulations and Physics‐Based Learning using a Surrogate Model for Soft Robot Control

Advanced Intelligent Systems, EarlyView.
A surrogate‐model‐based framework is proposed for combining high‐fidelity finite element method and efficient physics simulations to enable fast, accurate soft robot simulation for reinforcement learning, validated through sim‐to‐real experiments. Soft robotics holds immense promise for applications requiring adaptability and compliant interactions ...
Taehwa Hong, Jungjae Lee, Byung‐Hyun Song, Yong‐Lae Park   +3 more
wiley   +1 more source

Parametric Surfaces for Elliptic and Hyperbolic Geometries

Mathematics
Background/Objectives: In computer graphics, virtual worlds are constructed and visualized through algorithmic processes. These environments are typically populated with objects defined by mathematical models, traditionally based on Euclidean geometry ...
László Szirmay-Kalos, András Fridvalszky, László Szécsi, Márton Vaitkus   +3 more
doaj   +1 more source

Phase‐Change Alloys Enable Localized Reversible Stiffening and Actuation in Steerable Eversion Tip‐Growing Robots

Advanced Intelligent Systems, EarlyView.
This work presents a tip‐growing eversion robot that uses phase‐changing alloys for reversible stiffening and localized actuation, achieving 43× stiffness modulation, 15× force amplification, and segmental steering. The system enables precise navigation and force delivery in constrained, tortuous pathways.
Shamsa Al Harthy, S.M.Hadi Sadati, Shannon C. Stockdale, Radhouene Neji, Christos Bergeles   +4 more
wiley   +1 more source

Logarithmic corrections for near-extremal black holes

Journal of High Energy Physics
We present the computation of logarithmic corrections to near-extremal black hole entropy from one-loop Euclidean gravity path integral around the near-horizon geometry. We extract these corrections employing a suitably modified heat kernel method, where
Nabamita Banerjee, Muktajyoti Saha, Suthanth Srinivasan   +2 more
doaj   +1 more source

Determining Levels of Affective States with Riemannian Geometry Applied to EEG Signals

Applied Sciences
Emotion recognition from electroencephalography (EEG) often relies on Euclidean features that ignore the curved geometry of covariance matrices. We introduce a Riemannian-manifold pipeline which, combined with the Fisher Geodesic Minimum Distance to Mean
Agnieszka Wosiak, Anita Tereszczuk, Katarzyna Żykwińska   +2 more
doaj   +1 more source