Results 181 to 190 of about 247,097 (248)

Agent-based simulation for multi-resource-constrained scheduling of scattered atypical repetitive projects. [PDF]

Sci Rep
Sultan RA, Hamdy K, Essawy YAS.
europepmc   +1 more source

Compact Modeling of Volatile‐Switching Electrochemical Metallization Memory Cells by Means of the Electromotive Force

Advanced Intelligent Systems, EarlyView.
A volatile‐switching compact model of electrochemical metallization memory cells for neuromorphic architecture is developed and validated by reliable reproduction of device characterization measurements: I−V sweeps, SET kinetics, relaxation dynamics.
Rana Walied Ahmad, Solomon Amsalu Chekol, Julius Rasbach, Susanne Hoffmann‐Eifert, Stephan Menzel   +4 more
wiley   +1 more source

Variational approach to open quantum systems with long-range competing interactions. [PDF]

Commun Phys
Hryniuk DA, Szymańska MH.
europepmc   +1 more source

Machine Learning‐Driven Variability Analysis of Process Parameters for Semiconductor Manufacturing

Advanced Intelligent Systems, EarlyView.
This research presents a machine learning approach that integrates nonlinear variation decomposition (NLVD) with statistical techniques to quantify the contribution of individual unit processes to performance and variance of figure of merit (FoM) at the LOT level.
Sinyeong Kang, Hyeok Yun, Kyeongrae Cho, Seungjoon Eom, Soomin Kim, Seongsoo Jeong, Rockhyun Baek   +6 more
wiley   +1 more source

Bayesian hierarchical models for multivariate mixed responses with repeated measures: A case study in arterial occlusive disease. [PDF]

PLoS One
Ebrahim EA, Cengiz MA.
europepmc   +1 more source

Bayesian Optimisation for the Experimental Sciences: A Practical Guide to Data‐Efficient Optimisation of Laboratory Workflows

Advanced Intelligent Systems, EarlyView.
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, Martin Singull, T. Jesper Jacobsson   +2 more
wiley   +1 more source

An explainable GeoAI framework for spatial assessment of wildfire susceptibility in the Upper Ravi sub-basin, Indian Himalaya. [PDF]

Sci Rep
Suheb, Nawazuzzoha M, Ali MS, Rashid MM, Naqvi DF, Qaisar H, Sicard P, Karuppannan S, Naqvi HR.   +8 more
europepmc   +1 more source

Artificial Intelligence for Multiscale Modeling in Solid‐State Physics and Chemistry: A Comprehensive Review

Advanced Intelligent Systems, EarlyView.
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, Vitalii Kapitan, Andrey Ustyuzhanin   +2 more
wiley   +1 more source

Efficient Inference in First Passage Time Models. [PDF]

Stat Comput
Liu S, Fengler A, Frank MJ, Harrison MT.
europepmc   +1 more source

A Flexible and Energy‐Efficient Compute‐in‐Memory Accelerator for Kolmogorov–Arnold Networks

Advanced Intelligent Systems, EarlyView.
This article presents KA‐CIM, a compute‐in‐memory accelerator for Kolmogorov–Arnold Networks (KANs). It enables flexible and efficient computation of arbitrary nonlinear functions through cross‐layer co‐optimization from algorithm to device. KA‐CIM surpasses CPU, ASIC, VMM‐CIM, and prior KAN accelerators by 1–3 orders of magnitude in energy‐delay ...
Chirag Sudarshan, Oliver Artner, Paul‐Philipp Manea, Sebastian Siegel, Susanne Hoffmann‐Eifert, Regina Dittmann, John Paul Strachan   +6 more
wiley   +1 more source