Yee Whye Teh

Publications by Year

Research Areas

Bayesian Methods and Mixture Models, Gaussian Processes and Bayesian Inference, Machine Learning and Algorithms, Machine Learning and Data Classification, Neural Networks and Applications

Most-Cited Works

• → Hierarchical Dirichlet Processes(2006)3,539 cited
• Bayesian Learning via Stochastic Gradient Langevin Dynamics(2011)
• → Inferring the effectiveness of government interventions against COVID-19(2020)1,110 cited
• → The Concrete Distribution: A Continuous Relaxation of Discrete Random Variables(2016)1,036 cited
• → A Collapsed Variational Bayesian Inference Algorithm for Latent Dirichlet Allocation(2007)515 cited
• → A hierarchical Bayesian language model based on Pitman-Yor processes(2006)500 cited
• → On Smoothing and Inference for Topic Models(2012)452 cited
• Sharing Clusters among Related Groups: Hierarchical Dirichlet Processes(2004)
• → Set Transformer: A Framework for Attention-based Permutation-Invariant\n Neural Networks(2018)408 cited