Saved in:
| Main Authors: | Kaur, Jaspreet, Goyal, Meenu |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2411.06250 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Fractional $α$-Bernstein-Kantorovich operators of order $β$: A new construction and approximation results
by: Kaur, Jaspreet, et al.
Published: (2024)
by: Kaur, Jaspreet, et al.
Published: (2024)
Asymptotic properties for a general class of Szasz-Mirakjan-Durrmeyer operators
by: Abel, Ulrich, et al.
Published: (2024)
by: Abel, Ulrich, et al.
Published: (2024)
On the $L^p$-Convergence and Denoising Performance of Durrmeyer-Type Max-Min Neural Network Operators
by: Şahin, Berke, et al.
Published: (2026)
by: Şahin, Berke, et al.
Published: (2026)
Commutativity and spectral properties for a general class of Szasz-Mirakjan-Durrmeyer operators
by: Abel, Ulrich, et al.
Published: (2024)
by: Abel, Ulrich, et al.
Published: (2024)
On the representation of energy-preserving quadratic operators with application to Operator Inference
by: Gkimisis, Leonidas, et al.
Published: (2025)
by: Gkimisis, Leonidas, et al.
Published: (2025)
Spectral Approximation to Fractional Integral Operators
by: Liu, Xiaolin, et al.
Published: (2025)
by: Liu, Xiaolin, et al.
Published: (2025)
Approximation by Certain Complex Nevai Operators : Theory and Applications
by: Majethiya, Priyanka, et al.
Published: (2025)
by: Majethiya, Priyanka, et al.
Published: (2025)
Exponential Convergence of Deep Composite Polynomial Approximation for Cusp-Type Functions
by: Yeon, Kingsley, et al.
Published: (2025)
by: Yeon, Kingsley, et al.
Published: (2025)
Universal Approximation of Operators with Transformers and Neural Integral Operators
by: Zappala, Emanuele, et al.
Published: (2024)
by: Zappala, Emanuele, et al.
Published: (2024)
Convergence Analysis of Block Newton Methods for 1D Shallow Neural Network Approximation
by: Cai, Zhiqiang, et al.
Published: (2026)
by: Cai, Zhiqiang, et al.
Published: (2026)
Approximating Analytic Spectra of Hyperbolic Systems with Summation-by-Parts Finite Difference Operators
by: Erickson, Brittany A.
Published: (2024)
by: Erickson, Brittany A.
Published: (2024)
Convergence Rates for the Trotter Splitting for Unbounded Operators
by: Becker, Simon, et al.
Published: (2024)
by: Becker, Simon, et al.
Published: (2024)
Approximation properties of neural ODEs
by: De Marinis, Arturo, et al.
Published: (2025)
by: De Marinis, Arturo, et al.
Published: (2025)
Guaranteed Stable Quadratic Models and their applications in SINDy and Operator Inference
by: Goyal, Pawan, et al.
Published: (2023)
by: Goyal, Pawan, et al.
Published: (2023)
A Numerical Study of Combining RBF Interpolation and Finite Differences to Approximate Differential Operators
by: Rogan, Adrijan, et al.
Published: (2025)
by: Rogan, Adrijan, et al.
Published: (2025)
On the Convergence of a Spline Collocation Method for Nonlinear Fractional Boundary Value Problems with the Riesz-Caputo Operator
by: Sorgentone, Chiara, et al.
Published: (2026)
by: Sorgentone, Chiara, et al.
Published: (2026)
Numerical Approximations and Convergence Analysis of Piecewise Diffusion Markov Processes, with Application to Glioma Cell Migration
by: Buckwar, Evelyn, et al.
Published: (2024)
by: Buckwar, Evelyn, et al.
Published: (2024)
Quantitative Approximation for Neural Operators in Nonlinear Parabolic Equations
by: Furuya, Takashi, et al.
Published: (2024)
by: Furuya, Takashi, et al.
Published: (2024)
On the Approximation of Operator-Valued Riccati Equations in Hilbert Spaces
by: Cheung, James
Published: (2023)
by: Cheung, James
Published: (2023)
Guaranteed Approximation Bounds for Mixed-Precision Neural Operators
by: Tu, Renbo, et al.
Published: (2023)
by: Tu, Renbo, et al.
Published: (2023)
A PDE Perspective on Approximating Nonlocal Periodic Operators with Applications on Neural Networks for Critical SQG Equations
by: Abdo, Elie, et al.
Published: (2024)
by: Abdo, Elie, et al.
Published: (2024)
On a New Modification of Baskakov Operators with Higher Order of Approximation
by: Gadjev, Ivan, et al.
Published: (2024)
by: Gadjev, Ivan, et al.
Published: (2024)
Weak Convergence of Finite Element Approximations of Stochastic Linear Schrödinger equation driven by additive Wiener noise
by: Prasad, Mangala
Published: (2025)
by: Prasad, Mangala
Published: (2025)
Learning reduced-order Quadratic-Linear models in Process Engineering using Operator Inference
by: Gosea, Ion Victor, et al.
Published: (2024)
by: Gosea, Ion Victor, et al.
Published: (2024)
Convergence Rates for Learning Pseudo-Differential Operators
by: Chen, Jiaheng, et al.
Published: (2026)
by: Chen, Jiaheng, et al.
Published: (2026)
CUR Low Rank Approximation of a Matrix at Sublinear Cost
by: Go, Soo, et al.
Published: (2019)
by: Go, Soo, et al.
Published: (2019)
Universal Approximation of Nonlinear Operators and Their Derivatives
by: de Feo, Filippo
Published: (2026)
by: de Feo, Filippo
Published: (2026)
Dimension-Free Convergence of Diffusion Models for Approximate Gaussian Mixtures
by: Li, Gen, et al.
Published: (2025)
by: Li, Gen, et al.
Published: (2025)
Operator SVD with Neural Networks via Nested Low-Rank Approximation
by: Ryu, J. Jon, et al.
Published: (2024)
by: Ryu, J. Jon, et al.
Published: (2024)
Fourier Neural Operators for Non-Markovian Processes:Approximation Theorems and Experiments
by: Lee, Wonjae, et al.
Published: (2025)
by: Lee, Wonjae, et al.
Published: (2025)
Kernel Methods for the Approximation of the Eigenfunctions of the Koopman Operator
by: Lee, Jonghyeon, et al.
Published: (2024)
by: Lee, Jonghyeon, et al.
Published: (2024)
Projection Methods for Operator Learning and Universal Approximation
by: Zappala, Emanuele
Published: (2024)
by: Zappala, Emanuele
Published: (2024)
Convergence of Calderón residuals
by: Hiptmair, Ralf, et al.
Published: (2025)
by: Hiptmair, Ralf, et al.
Published: (2025)
Approximating Numerical Fluxes Using Fourier Neural Operators for Hyperbolic Conservation Laws
by: Kim, Taeyoung, et al.
Published: (2024)
by: Kim, Taeyoung, et al.
Published: (2024)
A Deep Learning Framework for Multi-Operator Learning: Architectures and Approximation Theory
by: Weihs, Adrien, et al.
Published: (2025)
by: Weihs, Adrien, et al.
Published: (2025)
Approximation with SiLU Networks: Constant Depth and Exponential Rates for Basic Operations
by: Ayena, Koffi O.
Published: (2025)
by: Ayena, Koffi O.
Published: (2025)
A Posteriori Error Estimation Improved by a Reconstruction Operator for the Stokes Optimal Control Problem
by: Li, Jingshi, et al.
Published: (2025)
by: Li, Jingshi, et al.
Published: (2025)
A Kernel-based Stochastic Approximation Framework for Nonlinear Operator Learning
by: Yang, Jia-Qi, et al.
Published: (2025)
by: Yang, Jia-Qi, et al.
Published: (2025)
Convergence of the fully discrete JKO scheme
by: Hraivoronska, Anastasiia, et al.
Published: (2025)
by: Hraivoronska, Anastasiia, et al.
Published: (2025)
Method of Successive Approximations for Stochastic Optimal Control: Contractivity and Convergence
by: Taoufik, Safouane, et al.
Published: (2024)
by: Taoufik, Safouane, et al.
Published: (2024)
Similar Items
-
Fractional $α$-Bernstein-Kantorovich operators of order $β$: A new construction and approximation results
by: Kaur, Jaspreet, et al.
Published: (2024) -
Asymptotic properties for a general class of Szasz-Mirakjan-Durrmeyer operators
by: Abel, Ulrich, et al.
Published: (2024) -
On the $L^p$-Convergence and Denoising Performance of Durrmeyer-Type Max-Min Neural Network Operators
by: Şahin, Berke, et al.
Published: (2026) -
Commutativity and spectral properties for a general class of Szasz-Mirakjan-Durrmeyer operators
by: Abel, Ulrich, et al.
Published: (2024) -
On the representation of energy-preserving quadratic operators with application to Operator Inference
by: Gkimisis, Leonidas, et al.
Published: (2025)