NIPS Proceedingsβ

Ole Winther

17 Papers

  • A Disentangled Recognition and Nonlinear Dynamics Model for Unsupervised Learning (2017)
  • Hash Embeddings for Efficient Word Representations (2017)
  • Ladder Variational Autoencoders (2016)
  • Sequential Neural Models with Stochastic Layers (2016)
  • Bayesian Inference for Structured Spike and Slab Priors (2014)
  • Bayesian Sparse Factor Models and DAGs Inference and Comparison (2009)
  • Improving on Expectation Propagation (2008)
  • Expectation Consistent Free Energies for Approximate Inference (2004)
  • Variational Linear Response (2003)
  • Incremental Gaussian Processes (2002)
  • TAP Gibbs Free Energy, Belief Propagation and Sparsity (2001)
  • Computing with Finite and Infinite Networks (2000)
  • Ensemble Learning and Linear Response Theory for ICA (2000)
  • Efficient Approaches to Gaussian Process Classification (1999)
  • Mean Field Methods for Classification with Gaussian Processes (1998)
  • A Mean Field Algorithm for Bayes Learning in Large Feed-forward Neural Networks (1996)
  • The Effect of Correlated Input Data on the Dynamics of Learning (1996)