Results 41 to 50 of about 5,659,086 (164)
A note on the Dancer–Fučík spectra of the fractional p-Laplacian and Laplacian operators
We study the Dancer–Fučík spectrum of the fractional p-Laplacian operator. We construct an unbounded sequence of decreasing curves in the spectrum using a suitable minimax scheme. For p = 2, we present a very accurate local analysis.
Perera Kanishka +2 more
doaj +1 more source
AI‐Driven Cancer Multi‐Omics: A Review From the Data Pipeline Perspective
The exponential growth of cancer multi‐omics data brings opportunities and challenges for precision oncology. This review systematically examines AI's role in addressing these challenges, covering generative models, integration architectures, Explainable AI for clinical trust, clinical applications, and key directions for clinical translation.
Shilong Liu, Shunxiang Li, Kun Qian
wiley +1 more source
Generative Models in Inorganic Crystals Discovery and Inverse Design
Generative inverse‐design samples from the vast inorganic crystal design space by starting from target properties such as band gap, stability, and ion transport. This Review examines the representations, generative models, and validation workflows needed to translate candidate structures into stable, potentially synthesizable materials for applications
Tao Li +5 more
wiley +1 more source
Social Exchange and Reciprocal Integration Between Migrants and Locals at Work
ABSTRACT Workplaces are pivotal “contact zones” where migrants and locals negotiate access to jobs, resources, and recognition, yet HRM research has rarely examined how everyday encounters generate integrated relationships at work. This conceptual paper introduces reciprocal integration as a workplace‐anchored social exchange process: the emergent ...
Minna Paunova, Maribel Blasco
wiley +1 more source
Differential item functioning detection across multiple groups
Abstract Differential item functioning (DIF) can be investigated by estimating item response theory (IRT) parameters separately for different respondent groups, thus allowing for the detection of discrepancies in parameter estimates across groups. However, before comparing the estimates, it is necessary to convert them to a common metric due to the ...
Michela Battauz
wiley +1 more source
Computing Skinning Weights via Convex Duality
We present an alternate optimization method to compute bounded biharmonic skinning weights. Our method relies on a dual formulation, which can be optimized with a nonnegative linear least squares setup. Abstract We study the problem of optimising for skinning weights through the lens of convex duality.
J. Solomon, O. Stein
wiley +1 more source
Minimax regret and strategic uncertainty [PDF]
This paper introduces a new solution concept, a minimax regret equilibrium, which allows for the possibility that players are uncertain about the rationality and conjectures of their opponents. We provide several applications of our concept.
Karl Schlag, Ludovic Renou
core +2 more sources
A Non‐Parametric Framework for Correlation Functions on Product Metric Spaces
Summary We propose a non‐parametric framework for analysing data defined over products of metric spaces, a versatile class encountered in various fields. This framework accommodates non‐stationarity and seasonality and is applicable to both local and global domains, such as the Earth's surface, as well as domains evolving over linear time or time ...
Pier Giovanni Bissiri +3 more
wiley +1 more source
Testing Distributional Granger Causality With Entropic Optimal Transport
ABSTRACT We develop a novel nonparametric test for Granger causality in distribution based on entropic optimal transport. Unlike classical mean‐based approaches, the proposed method directly compares the full conditional distributions of a response variable with and without the history of a candidate predictor.
Tao Wang
wiley +1 more source
ABSTRACT Generative adversarial networks (GANs) are artificial intelligence models designed to generate novel data that is indistinguishable from real data. Originally developed to generate images to complement existing datasets and create more diverse samples, GAN‐based data can enhance downstream analysis for machine learning and deep learning ...
Edgar Caballero Vargas, Tiago Bresolin
wiley +1 more source

