Code associated with the paper: Learning data-driven discretizations for partial differential equations. Yohai Bar-Sinai, Stephan Hoyer, Jason Hickey, Michael P. Brenner. Proceedings of the National ...

PDF for mathematics from the official Punjab Board website. Access chapter-wise details for mathematics with the link to ...

1906 Topics equation, differential, equations, solution, integral, linear, method, sin, general, arbitrary, differential equations, differential equation, general solution, partial differential, ...

Dear Editor, This letter addresses the critical challenge of preserving privacy in graph learning without compromising on data utility. Differential privacy (DP) is emerging as an effective method for ...

Differential equations and their applications : an introduction to applied mathematics by Braun, Martin, 1941- Publication date 1993 Topics Differential equations Publisher New York : Springer-Verlag ...

Partial differential equations (PDEs) are a class of mathematical problems that represent the interplay of multiple variables, and therefore have predictive power when it comes to complex physical ...

Uncertain differential equations are a type of differential equations driven by Liu processes. How to estimate the parameters in an uncertain differential equation based on the observed data is a ...

SUNDIALS: SUite of Nonlinear and DIfferential/ALgebraic equation Solvers Version 7.4.0 (Jun 2025) Center for Applied Scientific Computing, Lawrence Livermore National Laboratory SUNDIALS is a family ...