CITATION.cff

cff-version: 1.2.0
title: 3d_very_deep_vae
message: Please cite this software using these metadata.
type: software
authors:
  - given-names: Robert
    family-names: Gray
    email: r.gray@ucl.ac.uk
    affiliation: University College London
  - given-names: Matthew
    name-particle: M
    family-names: Graham
    email: m.graham@ucl.ac.uk
    affiliation: University College London
    orcid: 'https://orcid.org/0000-0001-9104-7960'
  - given-names: M Jorge
    family-names: Cardoso
    email: m.jorge.cardoso@kcl.ac.uk
    affiliation: King's College London
    orcid: 'https://orcid.org/0000-0003-1284-2558'
  - given-names: Sebastien
    family-names: Ourselin
    email: sebastien.ourselin@kcl.ac.uk
    affiliation: King's College London
    orcid: 'https://orcid.org/0000-0002-5694-5340'
  - given-names: Geraint
    family-names: Rees
    email: g.rees@ucl.ac.uk
    affiliation: University College London
    orcid: 'https://orcid.org/0000-0002-9623-7007'
  - given-names: Parashkev
    family-names: Nachev
    email: p.nachev@ucl.ac.uk
    affiliation: King's College London
    orcid: 'https://orcid.org/0000-0002-2718-4423'
doi: 10.5281/zenodo.6782948
repository-code: 'https://github.com/r-gray/3d_very_deep_vae'
abstract: >-
  PyTorch implementations of variational autoencoder
  models for generating synthetic three-dimensional
  images based on neuroimaging training data
keywords:
  - pytorch
  - variational autoencoder
  - neuroimaging
  - generative model
license: GPL-3.0