---
_id: '14224'
abstract:
- lang: eng
  text: Clustering is a cornerstone of unsupervised learning which can be thought
    as disentangling multiple generative mechanisms underlying the data. In this paper
    we introduce an algorithmic framework to train mixtures of implicit generative
    models which we particularize for variational autoencoders. Relying on an additional
    set of discriminators, we propose a competitive procedure in which the models
    only need to approximate the portion of the data distribution from which they
    can produce realistic samples. As a byproduct, each model is simpler to train,
    and a clustering interpretation arises naturally from the partitioning of the
    training points among the models. We empirically show that our approach splits
    the training distribution in a reasonable way and increases the quality of the
    generated samples.
article_processing_charge: No
arxiv: 1
author:
- first_name: Francesco
  full_name: Locatello, Francesco
  id: 26cfd52f-2483-11ee-8040-88983bcc06d4
  last_name: Locatello
  orcid: 0000-0002-4850-0683
- first_name: Damien
  full_name: Vincent, Damien
  last_name: Vincent
- first_name: Ilya
  full_name: Tolstikhin, Ilya
  last_name: Tolstikhin
- first_name: Gunnar
  full_name: Ratsch, Gunnar
  last_name: Ratsch
- first_name: Sylvain
  full_name: Gelly, Sylvain
  last_name: Gelly
- first_name: Bernhard
  full_name: Scholkopf, Bernhard
  last_name: Scholkopf
citation:
  ama: 'Locatello F, Vincent D, Tolstikhin I, Ratsch G, Gelly S, Scholkopf B. Clustering
    meets implicit generative models. In: <i>6th International Conference on Learning
    Representations</i>. ; 2018.'
  apa: Locatello, F., Vincent, D., Tolstikhin, I., Ratsch, G., Gelly, S., &#38; Scholkopf,
    B. (2018). Clustering meets implicit generative models. In <i>6th International
    Conference on Learning Representations</i>. Vancouver, Canada.
  chicago: Locatello, Francesco, Damien Vincent, Ilya Tolstikhin, Gunnar Ratsch, Sylvain
    Gelly, and Bernhard Scholkopf. “Clustering Meets Implicit Generative Models.”
    In <i>6th International Conference on Learning Representations</i>, 2018.
  ieee: F. Locatello, D. Vincent, I. Tolstikhin, G. Ratsch, S. Gelly, and B. Scholkopf,
    “Clustering meets implicit generative models,” in <i>6th International Conference
    on Learning Representations</i>, Vancouver, Canada, 2018.
  ista: Locatello F, Vincent D, Tolstikhin I, Ratsch G, Gelly S, Scholkopf B. 2018.
    Clustering meets implicit generative models. 6th International Conference on Learning
    Representations. International Conference on Machine Learning.
  mla: Locatello, Francesco, et al. “Clustering Meets Implicit Generative Models.”
    <i>6th International Conference on Learning Representations</i>, 2018.
  short: F. Locatello, D. Vincent, I. Tolstikhin, G. Ratsch, S. Gelly, B. Scholkopf,
    in:, 6th International Conference on Learning Representations, 2018.
conference:
  end_date: 2018-05-03
  location: Vancouver, Canada
  name: International Conference on Machine Learning
  start_date: 2018-04-30
date_created: 2023-08-22T14:25:34Z
date_published: 2018-05-01T00:00:00Z
date_updated: 2024-10-14T12:30:32Z
day: '01'
department:
- _id: FrLo
extern: '1'
external_id:
  arxiv:
  - '1804.11130'
language:
- iso: eng
main_file_link:
- open_access: '1'
  url: https://arxiv.org/abs/1804.11130
month: '05'
oa: 1
oa_version: Preprint
publication: 6th International Conference on Learning Representations
publication_status: published
quality_controlled: '1'
scopus_import: '1'
status: public
title: Clustering meets implicit generative models
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
year: '2018'
...