Zoubin Ghahramani

98 papers · 1999–2026 · 10 venues · across top CS/AI venues

This profile combines several different researchers. Authors are keyed by name, and this name's papers fall into 32 separate collaboration groups - the largest holds only 33% of them. Pick the group below that matches the researcher you mean. How a shared name is split.

Achievements are not shown for a combined profile - each one describes a single researcher's record, which this is not.

Which Zoubin Ghahramani?

4 groups of papers that share co-authors internally but none with each other - each most likely a different researcher. Pick one to see its papers.

with Isabel Valera, James Hensman, Yarin Gal 32 papers · 2014–2024 · ICML, NeurIPS, JMLR Show ▼

with Wei Chu, David Knowles, Ricardo Silva 22 papers · 1999–2017 · ICML, NeurIPS, AISTATS Hide ▲

A Birth-Death Process for Feature Allocation ICML 2017 Bayesian inference on random simple graphs with power law degree distributions ICML 2017 Pareto Frontier Learning with Expensive Correlated Objectives ICML 2016 An Empirical Study of Stochastic Variational Inference Algorithms for the Beta Bernoulli Process ICML 2015 Parallel Predictive Entropy Search for Batch Global Optimization of Expensive Objective Functions NeurIPS 2015 A reversible infinite HMM using normalised random measures ICML 2014 Beta Diffusion Trees ICML 2014 Student-t Processes as Alternatives to Gaussian Processes AISTATS 2014 Dynamic Probabilistic Models for Latent Feature Propagation in Social Networks ICML 2013 A nonparametric variable clustering model NeurIPS 2012 Testing a Bayesian Measure of Representativeness Using a Large Image Database NeurIPS 2011 The Indian Buffet Process: An Introduction and Review JMLR 2011 Large Scale Nonparametric Bayesian Inference: Data Parallelisation in the Indian Buffet Process NeurIPS 2009 The Hidden Life of Latent Variables: Bayesian Learning with Mixed Graph Models JMLR 2009 Bayesian Exponential Family PCA NeurIPS 2008 Hidden Common Cause Relations in Relational Learning NeurIPS 2007 Relational Learning with Gaussian Processes NeurIPS 2006 Factorial Mixture of Gaussians and the Marginal Independence Model AISTATS 2005 Gaussian Processes for Ordinal Regression JMLR 2005 Probabilistic Models for Incomplete Multi-dimensional Arrays AISTATS 2005 A Nonparametric Bayesian Approach to Modeling Overlapping Clusters AISTATS 1999 Analogical Reasoning with Relational Bayesian Sets AISTATS 1999

with José Miguel Hernández-Lobato, Neil Houlsby, Ryan P. Adams 14 papers · 2010–2016 · ICML, AISTATS, NeurIPS Show ▼

with Peter Orbanz, James Lloyd, Daniel M. Roy 2 papers · 2010–2012 · NeurIPS, AISTATS Show ▼

28 papers whose co-authors appear nowhere else under this name

Efficiently Reconstructing Dynamic Scenes One D4RT at a Time CVPR 2026 Pre-trained Gaussian Processes for Bayesian Optimization JMLR 2024 MetaGAN: An Adversarial Approach to Few-Shot Learning NeurIPS 2018 Bayesian Generalised Ensemble Markov Chain Monte Carlo AISTATS 2016 Distributed Flexible Nonlinear Tensor Factorization NeurIPS 2016 Linear Dimensionality Reduction: Survey, Insights, and Generalizations JMLR 2015 Statistical Model Criticism using Kernel Two Sample Tests NeurIPS 2015 A Non-parametric Conditional Factor Regression Model for Multi-Dimensional Input and Response AISTATS 2014 Randomized Nonlinear Component Analysis ICML 2014 Scalable Gaussian Process Structured Prediction for Grid Factor Graph Applications ICML 2014 A Nonparametric Bayesian Model for Multiple Clustering with Overlapping Feature Views AISTATS 2012 Active Learning of Model Evidence Using Bayesian Quadrature NeurIPS 2012 Bayesian Classifier Combination AISTATS 2012 Continuous Relaxations for Discrete Hamiltonian Monte Carlo NeurIPS 2012 Flexible Martingale Priors for Deep Hierarchies AISTATS 2012 Gaussian Processes for time-marked time-series data AISTATS 2012 (Invited Talk) Bayesian Hidden Markov Models and Extensions CoNLL 2010 Copula Processes NeurIPS 2010 Kronecker Graphs: An Approach to Modeling Networks JMLR 2010 The infinite HMM for unsupervised PoS tagging EMNLP 2009 The Infinite Factorial Hidden Markov Model NeurIPS 2008 Modeling Dyadic Data with Binary Latent Factors NeurIPS 2006 A kernel method for unsupervised structured network inference AISTATS 2005 Choosing a Variable to Clamp AISTATS 2005 The Block Diagonal Infinite Hidden Markov Model AISTATS 2005 Tree-Based Inference for Dirichlet Process Mixtures AISTATS 2005 Local and global sparse Gaussian process approximations AISTATS 1999 Stick-breaking Construction for the Indian Buffet Process AISTATS 1999

Venues · all papers under this name

ICML (28) NeurIPS (28) AISTATS (25) JMLR (10) AAAI (2) CoNLL (1) CVPR (1) EMNLP (1) ICLR (1) UAI (1)