https://cydb.mathematik.uni-mainz.de/
Calabi-Yau differential operator database v.3.0 - Search results
calabi yaudifferential operatorv 30 searchdatabase
https://www.mapleprimes.com/questions/233284-How-To-Act-With-A-Differential-Operator
How to act with a differential operator on a function - MaplePrimes
how to actdifferential operatorfunction
https://www.mdpi.com/2072-4292/15/16/3980
A Hybrid Binary Dragonfly Algorithm with an Adaptive Directed Differential Operator for Feature...
Feature selection is a typical multiobjective problem including two conflicting objectives. In classification, feature selection aims to improve or maintain...
https://www.nist.gov/publications/receiving-antenna-linear-differential-operatorapplication-spherical-near-field-scanning
The Receiving Antenna as a Linear Differential Operator:Application to Spherical Near-Field...
linear differential operator
https://openreview.net/forum?id=805jKZ0Gqf
Pseudo-Differential Neural Operator: Generalize Fourier Neural operator for Learning Solution...
Learning mapping between two function spaces has attracted considerable research attention. However, learning the solution operator of partial differential...
for learningpseudodifferentialneuraloperator
https://arxiv.org/abs/2312.17489
[2312.17489] Operator learning for hyperbolic partial differential equations
Abstract page for arXiv paper 2312.17489: Operator learning for hyperbolic partial differential equations
learning forpartial differential231217489operator
https://arxiv.org/abs/2506.13906v1
[2506.13906v1] GITO: Graph-Informed Transformer Operator for Learning Complex Partial Differential...
Abstract page for arXiv paper 2506.13906v1: GITO: Graph-Informed Transformer Operator for Learning Complex Partial Differential Equations
https://www.sintef.no/en/publications/publication/2282359/
Operator- and recurrent neural network learning for partial differential equations - SINTEF
recurrent neural networklearning forpartial differentialoperator
https://openreview.net/forum?id=dtYnHcmQKeM
Physics-Informed Neural Operator for Learning Partial Differential Equations | OpenReview
Machine learning methods have recently shown promise in solving partial differential equations (PDEs). They can be classified into two broad categories:...
for learningpartial differentialphysicsinformedneural
https://www.mapleprimes.com/questions/223552-How-Can-I-Get--And--To-Act-As-A-Simple
How can I get ' and '' to act as a simple superscript not a differential operator? - MaplePrimes
https://www.scirp.org/journal/paperinformation?paperid=125927
A Study on Stochastic Differential Equation Using Fractional Power of Operator in the Semigroup...
Explore the unpredictable behavior of continuous systems with stochastic differential equations (SDE). Discover how SDE combines differential equations,...
https://openreview.net/forum?id=c8P9NQVtmnO
Fourier Neural Operator for Parametric Partial Differential Equations | OpenReview
The classical development of neural networks has primarily focused on learning mappings between finite-dimensional Euclidean spaces. Recently, this has been...
partial differentialfourierneuraloperatorparametric