Giter Site home page Giter Site logo

skalarproduktraum / pde-learning Goto Github PK

View Code? Open in Web Editor NEW

This project forked from casus/pde-learning

0.0 0.0 0.0 3.16 MB

Learning Partial Differential Equations by Spectral Approximates of General Sobolev Spaces

Python 1.24% Jupyter Notebook 98.76%

pde-learning's Introduction

This framework contains the results submitted on the paper "Learning Partial Differential Equations by Spectral Approximates of General Sobolev Spaces",
submitted to Proceedings A Royal Society. ArXiv preprint is available, https://doi.org/10.48550/arXiv.2301.04887

The code was developed by Phil-Alexander Hofmann : [email protected], under the supervision of:
  - Juan-Esteban Suarez : [email protected]
  - Dr. Michael Hecht : [email protected]
All members of the Center for Advanced Systems Understanding (CASUS)

pde-learning's People

Contributors

juesuarezca avatar mikeypice avatar

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    ๐Ÿ–– Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. ๐Ÿ“Š๐Ÿ“ˆ๐ŸŽ‰

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google โค๏ธ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.