Results 101 to 110 of about 79,242 (197)

Target switching in 2D and 3D visual foraging reveals trade-offs between mental effort, travelling distance and movement speed. [PDF]

PLoS One
Orun E, Green RJ, De Lillo C.
europepmc   +1 more source

Bayesian Exploration of Metal‐Organic Framework‐Derived Nanocomposites for High‐Performance Supercapacitors

Advanced Intelligent Discovery, EarlyView.
An AI‐assisted approach is introduced to decode synthesis–performance relationships in metal‐organic framework‐derived supercapacitor materials using Bayesian optimization and predictive modeling, streamlining the search for optimal energy storage properties.
David Gryc, Pritam Banerjee, Felipe Jacques Lima Duarte, Joerg R. Jinschek, Premkumar Murugesan, Babak Rezaei, Stephan Sylvest Keller, Roland A. Fischer, Mian Zahid Hussain   +8 more
wiley   +1 more source

Solving High-Dimensional Dynamic Portfolio Choice Models with Hierarchical B-Splines on Sparse Grids

, 2019
Dirk Pflüger, Peter Schober, Julian Valentin   +2 more
openalex   +1 more source

SlingBAG: point cloud-based iterative algorithm for large-scale 3D photoacoustic imaging. [PDF]

Nat Commun
Li S, Wang Y, Gao J, Kim C, Choi S, Zhang Y, Chen Q, Yao Y, Li C.   +8 more
europepmc   +1 more source

Taguchi–Bayesian Sampling: A Roadmap for Polymer Database Construction Toward Small Representative Machine Learning

Advanced Intelligent Discovery, EarlyView.
This article establishes a Taguchi–Bayesian sampling strategy to reconstruct polymer processing–property landscape at minimal sampling cost, generically building the roadmap for materials database construction from sampling their vast design space. This sampling strategy is featured by an alternating lesson between uniformity and representativeness ...
Han Liu, Liantang Li
wiley   +1 more source

The rate of convergence of sparse grid quadrature on the torus

, 2011
Markus Hegland, Paul Leopardi
openalex   +2 more sources

A Dynamical Sparse Grid Collocation Method for Differential Equations Driven by White Noise [PDF]

, 2017
H. Cagan Ozen, Guillaume Bal
openalex   +1 more source

Gaussian Process Regression–Neural Network Hybrid with Optimized Redundant Coordinates: A New Simple Yet Potent Tool for Scientist's Machine Learning Toolbox

Advanced Intelligent Discovery, EarlyView.
A machine learning method, opt‐GPRNN, is presented that combines the advantages of neural networks and kernel regressions. It is based on additive GPR in optimized redundant coordinates and allows building a representation of the target with a small number of terms while avoiding overfitting when the number of terms is larger than optimal.
Sergei Manzhos, Manabu Ihara
wiley   +1 more source

A deep dictionary clustering approach for unsupervised image retrieval using convolutional sparse coding. [PDF]

Sci Rep
Sucharitha G, Vikas B, Reddy PVB, Suneel S, Divya N, Osman O, Rasheed J.   +6 more
europepmc   +1 more source

RAMS: Residual‐Based Adversarial‐Gradient Moving Sample Method for Scientific Machine Learning in Solving Partial Differential Equations

Advanced Intelligent Discovery, EarlyView.
We propose a residual‐based adversarial‐gradient moving sample (RAMS) method for scientific machine learning that treats samples as trainable variables and updates them to maximize the physics residual, thereby effectively concentrating samples in inadequately learned regions.
Weihang Ouyang, Min Zhu, Wei Xiong, Si‐Wei Liu, Lu Lu   +4 more
wiley   +1 more source