Teh, Yee W.

31 publications

NeurIPS 2021 BayesIMP: Uncertainty Quantification for Causal Data Fusion Siu Lun Chau, Jean-Francois Ton, Javier González, Yee W. Teh, Dino Sejdinovic

NeurIPS 2021 Group Equivariant Subsampling Jin Xu, Hyunjik Kim, Thomas Rainforth, Yee W. Teh

NeurIPS 2021 Neural Ensemble Search for Uncertainty Estimation and Dataset Shift Sheheryar Zaidi, Arber Zela, Thomas Elsken, Chris C Holmes, Frank Hutter, Yee W. Teh

NeurIPS 2021 On Contrastive Representations of Stochastic Processes Emile Mathieu, Adam Foster, Yee W. Teh

NeurIPS 2021 On Pathologies in KL-Regularized Reinforcement Learning from Expert Demonstrations Tim G. J. Rudner, Cong Lu, Michael A Osborne, Yarin Gal, Yee W. Teh

NeurIPS 2021 Powerpropagation: A Sparsity Inducing Weight Reparameterisation Jonathan Schwarz, Siddhant Jayakumar, Razvan Pascanu, Peter E Latham, Yee W. Teh

NeurIPS 2021 Vector-Valued Gaussian Processes on Riemannian Manifolds via Gauge Independent Projected Kernels Michael Hutchinson, Alexander Terenin, Viacheslav Borovitskiy, So Takao, Yee W. Teh, Marc Deisenroth

NeurIPS 2012 Bayesian Nonparametric Models for Ranked Data Francois Caron, Yee W. Teh

NeurIPS 2012 Learning Label Trees for Probabilistic Modelling of Implicit Feedback Andriy Mnih, Yee W. Teh

NeurIPS 2012 MCMC for Continuous-Time Discrete-State Systems Vinayak Rao, Yee W. Teh

NeurIPS 2012 Scalable Imputation of Genetic Data with a Discrete Fragmentation-Coagulation Process Lloyd Elliott, Yee W. Teh

NeurIPS 2012 Searching for Objects Driven by Context Bogdan Alexe, Nicolas Heess, Yee W. Teh, Vittorio Ferrari

NeurIPS 2011 Gaussian Process Modulated Renewal Processes Yee W. Teh, Vinayak Rao

NeurIPS 2011 Modelling Genetic Variations Using Fragmentation-Coagulation Processes Yee W. Teh, Charles Blundell, Lloyd Elliott

NeurIPS 2010 Improvements to the Sequence Memoizer Jan Gasthaus, Yee W. Teh

NeurIPS 2009 Indian Buffet Processes with Power-Law Behavior Yee W. Teh, Dilan Gorur

NeurIPS 2009 Spatial Normalized Gamma Processes Vinayak Rao, Yee W. Teh

NeurIPS 2008 A Mixture Model for the Evolution of Gene Expression in Non-Homogeneous Datasets Gerald Quon, Yee W. Teh, Esther Chan, Timothy Hughes, Michael Brudno, Quaid D. Morris

NeurIPS 2008 An Efficient Sequential Monte Carlo Algorithm for Coalescent Clustering Dilan Gorur, Yee W. Teh

NeurIPS 2008 Dependent Dirichlet Process Spike Sorting Jan Gasthaus, Frank Wood, Dilan Gorur, Yee W. Teh

NeurIPS 2008 The Infinite Factorial Hidden Markov Model Jurgen V. Gael, Yee W. Teh, Zoubin Ghahramani

NeurIPS 2008 The Mondrian Process Daniel M. Roy, Yee W. Teh

NeurIPS 2007 Bayesian Agglomerative Clustering with Coalescents Yee W. Teh, Hal Daume Iii, Daniel M. Roy

NeurIPS 2007 Collapsed Variational Inference for HDP Yee W. Teh, Kenichi Kurihara, Max Welling

NeurIPS 2007 Cooled and Relaxed Survey Propagation for MRFs Hai L. Chieu, Wee S. Lee, Yee W. Teh

NeurIPS 2006 A Collapsed Variational Bayesian Inference Algorithm for Latent Dirichlet Allocation Yee W. Teh, David Newman, Max Welling

NeurIPS 2004 Making Latin Manuscripts Searchable Using gHMM's Jaety Edwards, Yee W. Teh, Roger Bock, Michael Maire, Grace Vesom, David A. Forsyth

NeurIPS 2004 Sharing Clusters Among Related Groups: Hierarchical Dirichlet Processes Yee W. Teh, Michael I. Jordan, Matthew J. Beal, David M. Blei

NeurIPS 2003 Linear Response for Approximate Inference Max Welling, Yee W. Teh

NeurIPS 2002 Automatic Alignment of Local Representations Yee W. Teh, Sam T. Roweis

NeurIPS 2001 The Unified Propagation and Scaling Algorithm Yee W. Teh, Max Welling