NIPS Proceedingsβ

Richard Nock

8 Papers

  • A Primal-Dual link between GANs and Autoencoders (2019)
  • Disentangled behavioural representations (2019)
  • Representation Learning of Compositional Data (2018)
  • f-GANs in an Information Geometric Nutshell (2017)
  • A scaled Bregman theorem with applications (2016)
  • On Regularizing Rademacher Observation Losses (2016)
  • (Almost) No Label No Cry (2014)
  • On the Efficient Minimization of Classification Calibrated Surrogates (2008)