Results 91 to 100 of about 6,086,701 (288)
A Unifying Approach to Self‐Organizing Systems Interacting via Conservation Laws
Advanced Intelligent Discovery, EarlyView.The article develops a unified way to model and analyze self‐organizing systems whose interactions are constrained by conservation laws. It represents physical/biological/engineered networks as graphs and builds projection operators (from incidence/cycle structure) that enforce those constraints and decompose network variables into constrained versus ...
F. Barrows +7 more
wiley +1 more source
Advanced Intelligent Discovery, EarlyView.Phonons‐informed machine‐learning predictive models are propitious for reproducing thermal effects in computational materials science studies. Machine learning (ML) methods have become powerful tools for predicting material properties with near first‐principles accuracy and vastly reduced computational cost.
Pol Benítez +4 more
wiley +1 more source
Fragmentation, Zero Modes, and Collective Bound States in Constrained Models
PRX QuantumKinetically constrained models were originally introduced to capture slow relaxation in glassy systems, where dynamics are hindered by local constraints instead of energy barriers.
Eloi Nicolau +2 more
doaj +1 more source
Direction detector for distributed targets in unknown noise and interference [PDF]
, 2013 Adaptive detection of distributed radar targets in homogeneous Gaussian noise plus subspace interference is addressed. It is assumed that the actual steering vectors lie along a fixed and unknown direction of a preassigned and known subspace, while ...
Bandiera, Francesco +3 more
core +1 more source
Successive direction extraction for estimating the central subspace in a multiple-index regression
Journal of Multivariate Analysis, 2008 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Yin, Xiangrong +2 more
openaire +1 more source
Advanced Intelligent Discovery, EarlyView.This article outlines how artificial intelligence could reshape the design of next‐generation transistors as traditional scaling reaches its limits. It discusses emerging roles of machine learning across materials selection, device modeling, and fabrication processes, and highlights hierarchical reinforcement learning as a promising framework for ...
Shoubhanik Nath +4 more
wiley +1 more source
Advanced Intelligent Discovery, EarlyView.Materials informatics and autonomous experimentation are transforming the discovery of organic molecular crystals. This review presents an integrated molecule–crystal–function–optimization workflow combining machine learning, crystal structure prediction, and Bayesian optimization with robotic platforms.
Takuya Taniguchi +2 more
wiley +1 more source
Test function: A new approach for covering the central subspace
, 2011 In this paper we offer a complete methodology for sufficient dimension reduction called the test function (TF). TF provides a new family of methods for the estimation of the central subspace (CS) based on the introduction of a nonlinear transformation of the response.
Portier, François, Delyon, Bernard
openaire +3 more sources
A Language‐Guided Multimodal Foundation Model for Zero‐Shot and Multi‐Task Brain Signal Analysis
Advanced Intelligent Systems, EarlyView.METIS aligns brain signals with natural‐language instructions to enable zero‐shot and multi‐task brain signal analysis. Pretrained on over 70 000 h of EEG and iEEG recordings, it generalizes across sleep stage classification, epilepsy detection, and neurological disorder diagnosis, providing a scalable foundation model for clinically meaningful brain ...
Mingzhi Chen +3 more
wiley +1 more source
Dynamic determinants of the uncontrolled manifold during human quiet stance
Frontiers in Human Neuroscience, 2016 Human postural sway during stance arises from coordinated multi-joint movements. Thus, a sway trajectory represented by a time-varying postural vector in the multiple-joint-angle-space tends to be constrained to a low-dimensional subspace.
Yasuyuki Suzuki +4 more
doaj +1 more source