NIPS Proceedingsβ

Max Welling

23 Papers

  • Improved Variational Inference with Inverse Autoregressive Flow (2016)
  • Bayesian dark knowledge (2015)
  • Optimization Monte Carlo: Efficient and Embarrassingly Parallel Likelihood-Free Inference (2015)
  • Variational Dropout and the Local Reparameterization Trick (2015)
  • Semi-supervised Learning with Deep Generative Models (2014)
  • The Time-Marginalized Coalescent Prior for Hierarchical Clustering (2012)
  • Statistical Tests for Optimization Efficiency (2011)
  • On Herding and the Perceptron Cycling Theorem (2010)
  • Asynchronous Distributed Learning of Topic Models (2008)
  • Collapsed Variational Inference for HDP (2007)
  • Distributed Inference for Latent Dirichlet Allocation (2007)
  • Infinite State Bayes-Nets for Structured Domains (2007)
  • Accelerated Variational Dirichlet Process Mixtures (2006)
  • A Collapsed Variational Bayesian Inference Algorithm for Latent Dirichlet Allocation (2006)
  • Bayesian Model Scoring in Markov Random Fields (2006)
  • Products of ``Edge-perts (2005)
  • Exponential Family Harmoniums with an Application to Information Retrieval (2004)
  • Extreme Components Analysis (2003)
  • Linear Response for Approximate Inference (2003)
  • Wormholes Improve Contrastive Divergence (2003)
  • Learning Sparse Topographic Representations with Products of Student-t Distributions (2002)
  • Self Supervised Boosting (2002)
  • The Unified Propagation and Scaling Algorithm (2001)
  • 2 Books

  • Advances in Neural Information Processing Systems 27 (2014)
  • Advances in Neural Information Processing Systems 26 (2013)