Results 81 to 90 of about 1,712 (186)

A Multivariate Mixed‐Effects Regression Framework for Ground Motion Modeling: Integrating Parametric and Machine Learning Approaches

Earthquake Engineering &Structural Dynamics, Volume 55, Issue 9, Page 1811-1827, 25 July 2026.
ABSTRACT Multivariate ground motion models (GMMs) that capture the correlation between different intensity measures (IMs) are essential for seismic risk assessment. Conventional GMMs are often developed using a two‐stage approach, where separate univariate models with predefined functional forms are fitted first, and correlation is addressed in a ...
Sayed Mohammad Sajad Hussaini, Shaghayegh Karimzadeh, Paulo B. Lourenço   +2 more
wiley   +1 more source

Computing the Molecular Ground State Energy in a Restricted Active Space Using Quantum Annealing

Advanced Quantum Technologies, Volume 9, Issue 7, July 2026.
Can modern quantum annealers tackle realistic molecular problems? By combining XBK Hamiltonian mappings, next‐generation D‐Wave hardware, and advanced annealing protocols, significantly larger molecular instances become accessible with improved energy accuracy.
Stefano Bruni, Enrico Prati
wiley   +1 more source

Transformation Discriminant Analysis for Constructing Optimal Biomarker Combinations

Statistics in Medicine, Volume 45, Issue 15-17, July 2026.
ABSTRACT Accurate diagnostic tests are essential for effective screening and treatment. However, individual biomarkers often fail to provide sufficient diagnostic accuracy, as they typically capture only one aspect of the complex disease process. Combining multiple biomarkers, each capturing a distinct mechanism, can help construct more informative ...
Ainesh Sewak, Sandra Siegfried, Torsten Hothorn   +2 more
wiley   +1 more source

Markov Determinantal Point Process for Dynamic Random Sets

Journal of Time Series Analysis, Volume 47, Issue 4, Page 784-802, July 2026.
ABSTRACT The Law of Determinantal Point Process (LDPP) is a flexible parametric family of distributions over random sets defined on a finite state space, or equivalently over multivariate binary variables. The aim of this paper is to introduce Markov processes of random sets within the LDPP framework. We show that, when the pairwise distribution of two
Christian Gouriéroux, Yang Lu
wiley   +1 more source

RinQ: Towards predicting central sites in proteins on current quantum computers

Materials Today Quantum
We introduce RinQ, a hybrid quantum–classical framework for identifying functionally critical residues in proteins by formulating centrality detection as a Quadratic Unconstrained Binary Optimization (QUBO) problem.
Shah Ishmam Mohtashim
doaj   +1 more source

Solving Quadratic Unconstrained Binary Optimization with divide-and-conquer and quantum algorithms

CoRR, 2021
Quadratic Unconstrained Binary Optimization (QUBO) is a broad class of optimization problems with many practical applications. To solve its hard instances in an exact way, known classical algorithms require exponential time and several approximate methods have been devised to reduce such cost.
openaire   +2 more sources

Binary choice under asymmetric loss in a data‐rich environment: Theory and an application to algorithmic fairness

Quantitative Economics, Volume 17, Issue 3, Page 623-669, July 2026.
We study the binary choice problem in a data‐rich environment with asymmetric loss functions. The econometrics literature covers nonparametric binary choice problems but does not offer computationally attractive solutions in data‐rich environments. The machine learning literature has many algorithms but is focused mostly on loss functions that are ...
Andrii Babii, Xi Chen, Eric Ghysels, Rohit Kumar   +3 more
wiley   +1 more source

Triply‐Twinned Metamaterials: Unraveling the Mechanics and Failure Pathways Through High‐Resolution XCT

Advanced Materials, Volume 38, Issue 31, 2 June 2026.
Triply‐twinned architected lattices transform deformation from bending to stretching of struts, delivering up to threefold increases in stiffness and strength across polymeric and metallic systems. High‐resolution synchrotron XCT and image‐based simulations reveal how meta‐grain architecture, defects, and AM build orientation govern failure pathways ...
David McArthur, George Maddison, Jaianth Vijayakumar, Paul Tafforeau, Kathy Christofidou, Peter David Lee, PJ Tan, Chu Lun Alex Leung   +7 more
wiley   +1 more source

Old and new algorithms for polynomial unconstrained optimization problems in binary variables [PDF]

, 2023
Polynomial unconstrained optimization problems in binary variables (PUBO) are notoriously hard to solve. This talk presents an overview of recent advances which are revisiting ideas introduced more than 50 years ago.
Crama, Yves
core  

Quantum annealing and its variants: application to quadratic unconstrained binary optimization

, 2023
Published by RWTH Aachen University ...
openaire   +3 more sources