Results 91 to 100 of about 66,291 (256)

Max-Min Neural Network Operators For Approximation of Multivariate Functions

In this paper, we develop a multivariate framework for approximation by max-min neural network operators. Building on the recent advances in approximation theory by neural network operators, particularly, the univariate max-min operators, we propose and analyze new multivariate operators activated by sigmoidal functions.
Yadav, Abhishek, Singh, Uaday, Dai, Feng
openaire   +2 more sources

Overcoming the Nyquist Limit in Molecular Hyperspectral Imaging by Reinforcement Learning

Advanced Intelligent Discovery, EarlyView.
Explorative spectral acquisition guide automatically selects informative spectral bands to optimize downstream tasks, outperforming full‐spectrum acquisition. The selected hyperspectral data are used for tasks such as unmixing and segmentation. BandOptiNet encodes selection states and outputs optimal bands to guide spectral acquisition. Recent advances
Xiaobin Tang, Yongqing Zhang, Xinyu Deng, Hyeon Jeong Lee, Delong Zhang   +4 more
wiley   +1 more source

Deep Learning Approaches for Classifying Crack States With Overload and Predicting Fatigue Parameters in a Titanium Alloy

Advanced Intelligent Systems, EarlyView.
This study proposes a deep learning approach to evaluate the fatigue crack behavior in metals under overload conditions. Using digital image correlation to capture the strain near crack tips, convolutional neural networks classify crack states as normal, overload, or recovery, and accurately predict fatigue parameters.
Seon Du Choi, Suman Timilsina, Youn Woo Shin, Yong Nam Kwon, Kee‐Sun Sohn, Ji Sik Kim   +5 more
wiley   +1 more source

Recent Trends in Metabolomics by NMR Spectroscopy

Angewandte Chemie, EarlyView.
AI tools were applied to analyze more than 5 000 publications indexed in Scopus (2018–2025), identifying key trends and research directions in NMR‐based metabolomics. The artificial intelligence‐assisted workflow classified papers into six main fields of application, human health, food and nutrition, veterinary science, plants, environment, and ...
Giorgio Di Paco, Gaia Meoni, Veronica Ghini, Alessia Vignoli, Leonardo Tenori, Paola Turano, Claudio Luchinat   +6 more
wiley   +2 more sources

Optimizing 3D Bin Packing of Heterogeneous Objects Using Continuous Transformations in SE(3)

Advanced Intelligent Systems, EarlyView.
This article presents a method for solving the three‐dimensional bin packing problem for heterogeneous objects using continuous rigid‐body transformations in SE(3). A heuristic optimization framework combines signed‐distance functions, neural network approximations, point‐cloud bin modeling, and physics simulation to ensure feasibility and stability ...
Michele Angelini, Marco Carricato
wiley   +1 more source

Time‐Delayed Spiking Reservoir Computing Enables Efficient Time Series Prediction

Advanced Intelligent Systems, EarlyView.
This study proposes time‐delayed spiking reservoir computing (TDSRC) for efficient time series prediction. By concatenating time‐lagged states, TDSRC constructs an expanded readout feature vector without altering internal reservoir dynamics. This approach enables highly accurate forecasting with significantly fewer neurons, providing a resource ...
Pin Jin, Ren Cao, Zhongxue Gan, Siyang Leng   +3 more
wiley   +1 more source

On the Approximation Capabilities of Deep Neural Networks for Multivariate Time Series Modeling

CAUCHY: Jurnal Matematika Murni dan Aplikasi
Multivariate time series forecasting plays a crucial role in various domains, including finance, where accurate stock price prediction supports strategic decision-making. Traditional methods such as Autoregressive Integrated Moving Average (ARIMA), Exponential Smoothing (ETS), and Vector Autoregression (VAR) often fall short when dealing with complex ...
Mohammad Jamhuri, Mohammad Isa Irawan, Ari Kusumastuti, Kartick Chandra Mondal, Juhari Juhari   +4 more
openaire   +1 more source

High‐elevation endemic plants predicted to lose habitat from changing climate in Washington State

American Journal of Botany, EarlyView.
Abstract Premise High‐elevation plants face unique challenges from potential climate change impacts that will likely require upslope migration into increasingly smaller suitable habitat. This situation is particularly acute for endemic species that by definition occupy small geographic ranges.
Nicholas L. Gjording, Erik W. Ertsgaard, David E. Giblin, Iris H. Dimpsey, Owen B. Bard   +4 more
wiley   +1 more source

A Global Prospective Harmonization Framework for Suicidality, Anhedonia, and Obsessive‐Compulsive Symptoms in Psychiatric Genetic Studies: A Cross‐Continental Study Within the Ancestral Population Network

American Journal of Medical Genetics Part B: Neuropsychiatric Genetics, EarlyView.
ABSTRACT This study aims to prospectively collect harmonized, quantitative, and dimensional psychiatric phenotypes (suicidality, anhedonia, and obsessive‐compulsive symptoms) and information on discrimination, stigma, and unfair treatment in up to 27,500 individuals across diverse ancestries and clinical populations for genetic analysis within the NIMH
Ana M. Diaz‐Zuluaga, Jacey L. Anderberg, Ana M. Ramirez‐Diaz, Andrea Horvath Marques, Catherine E. Rast, Daniel Bustamante, Deborah Jonker, Johanna Valencia‐Echeverry, Joseph Kyebuzibwa, Josselyn S. Muñoz, Kristien van der Walt, Mauricio Castaño Ramirez, Olivia Wootton, Renee M. Frederick, Rocky E. Stroud II, Ruben Gur, Sang Jin Rhee, Shaili C. Jha, Stella Gichuru, Susan Service, Victor I. Reus, Akena Dickens, Carlos Lopez‐Jaramillo, Carrie E. Bearden, Dan J. Stein, Ezra S. Susser, James J. Crowley, Jonathan Flint, Kenneth S. Kendler, Lukoye Atwoli, Michele T. Pato, Nelson B. Freimer, Roel A. Ophoff, Yong Min Ahn, Loes Olde Loohuis, Eric A. Storch, Bizu Gelaye   +36 more
wiley   +1 more source

A software framework for automated behavioral modeling of electronic devices [PDF]

, 2012
De Zutter, Daniël, Deschrijver, Dirk, Dhaene, Tom, Gorissen, Dirk   +3 more
core   +1 more source