Results 121 to 130 of about 48,981 (245)

On Bounds for Norms of Reparameterized ReLU Artificial Neural Network Parameters: Sums of Fractional Powers of the Lipschitz Norm Control the Network Parameter Vector

Mathematical Methods in the Applied Sciences, Volume 49, Issue 4, Page 2135-2160, 15 March 2026.
ABSTRACT It is an elementary fact in the scientific literature that the Lipschitz norm of the realization function of a feedforward fully connected rectified linear unit (ReLU) artificial neural network (ANN) can, up to a multiplicative constant, be bounded from above by sums of powers of the norm of the ANN parameter vector.
Arnulf Jentzen, Timo Kröger
wiley   +1 more source

Quasiconformal circles and Lipschitz classes

Commentarii Mathematici Helvetici, 1980
Näkki, Raimo, Palka, Bruce
openaire   +2 more sources

Semiclassical inequalities for Dirichlet and Neumann Laplacians on convex domains

Communications on Pure and Applied Mathematics, Volume 79, Issue 3, Page 762-822, March 2026.
Abstract We are interested in inequalities that bound the Riesz means of the eigenvalues of the Dirichlet and Neumann Laplacians in terms of their semiclassical counterpart. We show that the classical inequalities of Berezin–Li–Yau and Kröger, valid for Riesz exponents γ≥1$\gamma \ge 1$, extend to certain values γ<1$\gamma <1$, provided the underlying ...
Rupert L. Frank, Simon Larson
wiley   +1 more source

Regularity Properties of Solutions of a Model for Morphoelastic Growth in the Presence of Nutrients in One Spatial Dimension

PAMM, Volume 26, Issue 1, March 2026.
ABSTRACT Regularity properties of solutions for a class of quasi‐stationary models in one spatial dimension for stress‐modulated growth in the presence of a nutrient field are proven. At a given point in time the configuration of a body after pure growth is determined by means of a family of ordinary differential equations in every point in space ...
Julian Blawid, Georg Dolzmann
wiley   +1 more source

Exploring Imprecise Probabilities in Quantum Algorithms with Possibility Theory

PAMM, Volume 26, Issue 1, March 2026.
ABSTRACT Quantum computing utilizes the underlying principles of quantum mechanics to perform computations with unmatched performance capabilities. Rather than using classical bits, it operates on qubits, which can exist in superposition and entangled states. This enables the solution of problems that are considered intractable for classical computers.
Jan Schneider, Tom Könecke, Michael Hanss   +2 more
wiley   +1 more source

Estimates for Durrmeyer-type exponential sampling series in Mellin-Orlicz spaces

Demonstratio Mathematica
This study examines Durrmeyer-type exponential sampling series to obtain a quantitative estimate by using the concept of the logarithmic modulus of smoothness defined with the help of a suitable modular functional on Mellin-Orlicz spaces.
Kangal Esma, Kantar Ülkü Dinlemez
doaj   +1 more source

Longitudinal Alzheimer’s Disease Progression Modelling via Hybrid Vision Transformers and Recurrent Neural Networks With Cross‐Modal Feature Fusion

Expert Systems, Volume 43, Issue 3, March 2026.
ABSTRACT Modelling the evolution of Alzheimer's disease (AD) requires a thorough spatiotemporal study of longitudinal neuroimaging data. We propose in this paper a novel deep learning framework that uses a parallel combination of Recurrent Neural Networks (RNNs) and Vision Transformers (ViT) to extract temporal disease dynamics and spatial structural ...
Sahbi Bahroun, Gwanggil Jeon
wiley   +1 more source

On goodness‐of‐fit testing for self‐exciting point processes

Scandinavian Journal of Statistics, Volume 53, Issue 1, Page 102-139, March 2026.
Abstract Despite the wide usage of parametric point processes in theory and applications, a sound goodness‐of‐fit procedure to test whether a given parametric model is appropriate for data coming from a self‐exciting point process has been missing in the literature.
José Carlos Fontanesi Kling, Mathias Vetter   +1 more
wiley   +1 more source

Variable selection via thresholding

Scandinavian Journal of Statistics, Volume 53, Issue 1, Page 207-237, March 2026.
Abstract Variable selection comprises an important step in many modern statistical inference procedures. In the regression setting, when estimators cannot shrink irrelevant signals to zero, covariates without relationships to the response often manifest small but nonzero regression coefficients.
Ka Long Keith Ho, Hien Duy Nguyen
wiley   +1 more source

Neural network‐based offset‐free model predictive control for nonlinear systems

AIChE Journal, Volume 72, Issue 2, February 2026.
Abstract This paper proposes an offset‐free model predictive control (MPC) framework for nonlinear systems modeled using neural network‐based nonlinear autoregressive models with exogenous inputs (NARX). To address plant‐model mismatch and ensure offset‐free tracking, the NARX model is augmented with an integrating disturbance model, resulting in an ...
Hesam Hassanpour, Prashant Mhaskar
wiley   +1 more source