NIPS Proceedings
β
Books
Ole Winther
18 Papers
Recurrent Relational Networks
(2018)
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)