CITATION.cff

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cff-version: 1.2.0
title: >-
  PyTorch Implementation of Physics Informed Neural Network
  (PINN)
message: >-
  If you use this software, please cite it using the
  metadata from this file.
type: software
authors:
  - given-names: Nandita
    family-names: Doloi
    email: nanditad48@gmail.com
    orcid: 'https://orcid.org/0009-0007-1948-004X'
identifiers:
  - type: url
    value: 'https://github.com/nanditadoloi/PINN'
    description: Github Code Repository
repository: >-
  https://onepetro.org/SPERCSC/proceedings-abstract/22RCSC/1-22RCSC/515732
abstract: >-
  This repository contains my simple and clear to understand
  implementation of the paper [1]. As an example, I solved
  the 1D heat partial differential equation.


  [1] Raissi, Maziar, Paris Perdikaris, and George E.
  Karniadakis. "Physics-informed neural networks: A deep
  learning framework for solving forward and inverse
  problems involving nonlinear partial differential
  equations." Journal of Computational Physics 378 (2019):
  686-707.
keywords:
  - pinn
  - pytorch
  - github
  - nandita doloi
license: MIT