Results 31 to 40 of about 11,706 (202)

Twisted convolution and Moyal star product of generalized functions

open access: yes, 2012
We consider nuclear function spaces on which the Weyl-Heisenberg group acts continuously and study the basic properties of the twisted convolution product of the functions with the dual space elements.
B. S. Mityagin   +38 more
core   +1 more source

Pointwise multipliers for Triebel–Lizorkin and Besov spaces on Lie groups

open access: yesBulletin des Sciences Mathématiques, 2023
30 ...
Tommaso Bruno   +2 more
openaire   +3 more sources

A Unifying Approach to Self‐Organizing Systems Interacting via Conservation Laws

open access: yesAdvanced Intelligent Discovery, EarlyView.
The article develops a unified way to model and analyze self‐organizing systems whose interactions are constrained by conservation laws. It represents physical/biological/engineered networks as graphs and builds projection operators (from incidence/cycle structure) that enforce those constraints and decompose network variables into constrained versus ...
F. Barrows   +7 more
wiley   +1 more source

Retinal Vessel Segmentation: A Comprehensive Review From Classical Methods to Deep Learning Advances (1982–2025)

open access: yesAdvanced Intelligent Systems, EarlyView.
Four decades of retinal vessel segmentation research (1982–2025) are synthesized, spanning classical image processing, machine learning, and deep learning paradigms. A meta‐analysis of 428 studies establishes a unified taxonomy and highlights performance trends, generalization capabilities, and clinical relevance.
Avinash Bansal   +6 more
wiley   +1 more source

A Latent Source Model for Patch-Based Image Segmentation

open access: yes, 2015
Despite the popularity and empirical success of patch-based nearest-neighbor and weighted majority voting approaches to medical image segmentation, there has been no theoretical development on when, why, and how well these nonparametric methods work.
Chen, George   +2 more
core   +1 more source

Disentangling Aleatoric and Epistemic Uncertainty in Physics‐Informed Neural Networks: Application to Insulation Material Degradation Prognostics

open access: yesAdvanced Intelligent Systems, EarlyView.
Physics‐Informed Neural Networks (PINNs) provide a framework for integrating physical laws with data. However, their application to Prognostics and Health Management (PHM) remains constrained by the limited uncertainty quantification (UQ) capabilities.
Ibai Ramirez   +4 more
wiley   +1 more source

Seeds of change: The impact of Ethiopia's direct seed marketing approach on smallholders' seed purchases and productivity

open access: yesAmerican Journal of Agricultural Economics, EarlyView.
Abstract While multiple factors explain low adoption rates of improved varieties by small‐scale farmers in sub‐Saharan Africa, a key supply‐side constraint is the limited availability of seed embodying new traits in the volume, quality, price, and timeliness required by farmers. This constraint is partly attributable to classical failures in the market
Dawit Mekonnen   +5 more
wiley   +1 more source

Local stability and a renormalized Newton Method for equilibrium liquid crystal director modeling [PDF]

open access: yes, 2012
We consider the nonlinear systems of equations that result from discretizations of a prototype variational model for the equilibrium director field characterizing the orientational properties of a liquid crystal material.
Gartland, Jr, E.C., Ramage, Alison
core  

Restricted Tweedie stochastic block models

open access: yesCanadian Journal of Statistics, EarlyView.
Abstract The stochastic block model (SBM) is a widely used framework for community detection in networks, where the network structure is typically represented by an adjacency matrix. However, conventional SBMs are not directly applicable to an adjacency matrix that consists of nonnegative zero‐inflated continuous edge weights.
Jie Jian, Mu Zhu, Peijun Sang
wiley   +1 more source

Invariant Measure and Universality of the 2D Yang–Mills Langevin Dynamic

open access: yesCommunications on Pure and Applied Mathematics, EarlyView.
ABSTRACT We prove that the Yang–Mills (YM) measure for the trivial principal bundle over the two‐dimensional torus, with any connected, compact structure group, is invariant for the associated renormalised Langevin dynamic. Our argument relies on a combination of regularity structures, lattice gauge‐fixing and Bourgain's method for invariant measures ...
Ilya Chevyrev, Hao Shen
wiley   +1 more source

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