NIPS Proceedingsβ

Yee W. Teh

24 Papers

  • Bayesian nonparametric models for ranked data (2012)
  • Learning Label Trees for Probabilistic Modelling of Implicit Feedback (2012)
  • MCMC for continuous-time discrete-state systems (2012)
  • Scalable imputation of genetic data with a discrete fragmentation-coagulation process (2012)
  • Searching for objects driven by context (2012)
  • Gaussian process modulated renewal processes (2011)
  • Modelling Genetic Variations using Fragmentation-Coagulation Processes (2011)
  • Improvements to the Sequence Memoizer (2010)
  • Indian Buffet Processes with Power-law Behavior (2009)
  • Spatial Normalized Gamma Processes (2009)
  • A mixture model for the evolution of gene expression in non-homogeneous datasets (2008)
  • An Efficient Sequential Monte Carlo Algorithm for Coalescent Clustering (2008)
  • Dependent Dirichlet Process Spike Sorting (2008)
  • The Infinite Factorial Hidden Markov Model (2008)
  • The Mondrian Process (2008)
  • Bayesian Agglomerative Clustering with Coalescents (2007)
  • Collapsed Variational Inference for HDP (2007)
  • Cooled and Relaxed Survey Propagation for MRFs (2007)
  • A Collapsed Variational Bayesian Inference Algorithm for Latent Dirichlet Allocation (2006)
  • Making Latin Manuscripts Searchable using gHMM's (2004)
  • Sharing Clusters among Related Groups: Hierarchical Dirichlet Processes (2004)
  • Linear Response for Approximate Inference (2003)
  • Automatic Alignment of Local Representations (2002)
  • The Unified Propagation and Scaling Algorithm (2001)