Ghahramani, Zoubin

171 publications

JMLR 2024 Pre-Trained Gaussian Processes for Bayesian Optimization Zi Wang, George E. Dahl, Kevin Swersky, Chansoo Lee, Zachary Nado, Justin Gilmer, Jasper Snoek, Zoubin Ghahramani

JMLR 2024 Resource-Efficient Neural Networks for Embedded Systems Wolfgang Roth, Günther Schindler, Bernhard Klein, Robert Peharz, Sebastian Tschiatschek, Holger Fröning, Franz Pernkopf, Zoubin Ghahramani

ICML 2023 Neural Diffusion Processes Vincent Dutordoir, Alan Saul, Zoubin Ghahramani, Fergus Simpson

ICMLW 2022 Plex: Towards Reliability Using Pretrained Large Model Extensions Dustin Tran, Jeremiah Zhe Liu, Michael W Dusenberry, Du Phan, Mark Collier, Jie Ren, Kehang Han, Zi Wang, Zelda E Mariet, Huiyi Hu, Neil Band, Tim G. J. Rudner, Karan Singhal, Zachary Nado, Joost van Amersfoort, Andreas Kirsch, Rodolphe Jenatton, Nithum Thain, Honglin Yuan, E. Kelly Buchanan, Kevin Patrick Murphy, D. Sculley, Yarin Gal, Zoubin Ghahramani, Jasper Snoek, Balaji Lakshminarayanan

NeurIPS 2021 Deep Neural Networks as Point Estimates for Deep Gaussian Processes Vincent Dutordoir, James Hensman, Mark van der Wilk, Carl Henrik Ek, Zoubin Ghahramani, Nicolas Durrande

ICML 2020 Einsum Networks: Fast and Scalable Learning of Tractable Probabilistic Circuits Robert Peharz, Steven Lang, Antonio Vergari, Karl Stelzner, Alejandro Molina, Martin Trapp, Guy Van Den Broeck, Kristian Kersting, Zoubin Ghahramani

JMLR 2020 General Latent Feature Models for Heterogeneous Datasets Isabel Valera, Melanie F. Pradier, Maria Lomeli, Zoubin Ghahramani

AAAI 2019 Automatic Bayesian Density Analysis Antonio Vergari, Alejandro Molina, Robert Peharz, Zoubin Ghahramani, Kristian Kersting, Isabel Valera

NeurIPS 2019 Bayesian Learning of Sum-Product Networks Martin Trapp, Robert Peharz, Hong Ge, Franz Pernkopf, Zoubin Ghahramani

AAAI 2019 One-Network Adversarial Fairness Tameem Adel, Isabel Valera, Zoubin Ghahramani, Adrian Weller

UAI 2019 Random Sum-Product Networks: A Simple and Effective Approach to Probabilistic Deep Learning Robert Peharz, Antonio Vergari, Karl Stelzner, Alejandro Molina, Xiaoting Shao, Martin Trapp, Kristian Kersting, Zoubin Ghahramani

ICML 2018 Discovering Interpretable Representations for Both Deep Generative and Discriminative Models Tameem Adel, Zoubin Ghahramani, Adrian Weller

ICLR 2018 Gaussian Process Behaviour in Wide Deep Neural Networks Alexander G. de G. Matthews, Jiri Hron, Mark Rowland, Richard E. Turner, Zoubin Ghahramani

NeurIPS 2018 MetaGAN: An Adversarial Approach to Few-Shot Learning Ruixiang Zhang, Tong Che, Zoubin Ghahramani, Yoshua Bengio, Yangqiu Song

ICML 2018 The Mirage of Action-Dependent Baselines in Reinforcement Learning George Tucker, Surya Bhupatiraju, Shixiang Gu, Richard Turner, Zoubin Ghahramani, Sergey Levine

AISTATS 2018 Turing: Composable Inference for Probabilistic Programming Hong Ge, Kai Xu, Zoubin Ghahramani

ICML 2018 Variational Bayesian Dropout: Pitfalls and Fixes Jiri Hron, Alex Matthews, Zoubin Ghahramani

AAAI 2018 Weakly Supervised Collective Feature Learning from Curated Media Yusuke Mukuta, Akisato Kimura, David B. Adrian, Zoubin Ghahramani

ICML 2017 A Birth-Death Process for Feature Allocation Konstantina Palla, David Knowles, Zoubin Ghahramani

ICML 2017 Automatic Discovery of the Statistical Types of Variables in a Dataset Isabel Valera, Zoubin Ghahramani

ICML 2017 Bayesian Inference on Random Simple Graphs with Power Law Degree Distributions Juho Lee, Creighton Heaukulani, Zoubin Ghahramani, Lancelot F. James, Seungjin Choi

ICML 2017 Deep Bayesian Active Learning with Image Data Yarin Gal, Riashat Islam, Zoubin Ghahramani

MLOSS 2017 GPflow: A Gaussian Process Library Using TensorFlow Alexander G. de G. Matthews, Mark van der Wilk, Tom Nickson, Keisuke Fujii, Alexis Boukouvalas, Pablo León-Villagrá, Zoubin Ghahramani, James Hensman

NeurIPS 2017 Interpolated Policy Gradient: Merging On-Policy and Off-Policy Gradient Estimation for Deep Reinforcement Learning Shixiang Gu, Timothy Lillicrap, Richard E Turner, Zoubin Ghahramani, Bernhard Schölkopf, Sergey Levine

ICML 2017 Lost Relatives of the Gumbel Trick Matej Balog, Nilesh Tripuraneni, Zoubin Ghahramani, Adrian Weller

ICML 2017 Magnetic Hamiltonian Monte Carlo Nilesh Tripuraneni, Mark Rowland, Zoubin Ghahramani, Richard Turner

ICLR 2017 Q-Prop: Sample-Efficient Policy Gradient with an Off-Policy Critic Shixiang Gu, Timothy P. Lillicrap, Zoubin Ghahramani, Richard E. Turner, Sergey Levine

JMLR 2016 A General Framework for Constrained Bayesian Optimization Using Information-Based Search José Miguel Hernández-Lobato, Michael A. Gelbart, Ryan P. Adams, Matthew W. Hoffman, Zoubin Ghahramani

NeurIPS 2016 A Theoretically Grounded Application of Dropout in Recurrent Neural Networks Yarin Gal, Zoubin Ghahramani

AISTATS 2016 Bayesian Generalised Ensemble Markov Chain Monte Carlo Jes Frellsen, Ole Winther, Zoubin Ghahramani, Jesper Ferkinghoff-Borg

NeurIPS 2016 Distributed Flexible Nonlinear Tensor Factorization Shandian Zhe, Kai Zhang, Pengyuan Wang, Kuang-chih Lee, Zenglin Xu, Yuan Qi, Zoubin Ghahramani

ICML 2016 Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Yarin Gal, Zoubin Ghahramani

UAI 2016 Markov Beta Processes for Time Evolving Dictionary Learning Amar Shah, Zoubin Ghahramani

AISTATS 2016 On Sparse Variational Methods and the Kullback-Leibler Divergence Between Stochastic Processes Alexander G. de G. Matthews, James Hensman, Richard E. Turner, Zoubin Ghahramani

ICML 2016 Pareto Frontier Learning with Expensive Correlated Objectives Amar Shah, Zoubin Ghahramani

ICML 2016 Scalable Discrete Sampling as a Multi-Armed Bandit Problem Yutian Chen, Zoubin Ghahramani

UAI 2016 The Mondrian Kernel Matej Balog, Balaji Lakshminarayanan, Zoubin Ghahramani, Daniel M. Roy, Yee Whye Teh

ICML 2015 A Probabilistic Model for Dirty Multi-Task Feature Selection Daniel Hernandez-Lobato, Jose Miguel Hernandez-Lobato, Zoubin Ghahramani

ICML 2015 An Empirical Study of Stochastic Variational Inference Algorithms for the Beta Bernoulli Process Amar Shah, David Knowles, Zoubin Ghahramani

ICML 2015 Distributed Inference for Dirichlet Process Mixture Models Hong Ge, Yutian Chen, Moquan Wan, Zoubin Ghahramani

ICML 2015 Latent Gaussian Processes for Distribution Estimation of Multivariate Categorical Data Yarin Gal, Yutian Chen, Zoubin Ghahramani

JMLR 2015 Linear Dimensionality Reduction: Survey, Insights, and Generalizations John P. Cunningham, Zoubin Ghahramani

NeurIPS 2015 MCMC for Variationally Sparse Gaussian Processes James Hensman, Alexander G Matthews, Maurizio Filippone, Zoubin Ghahramani

NeurIPS 2015 Neural Adaptive Sequential Monte Carlo Shixiang Gu, Zoubin Ghahramani, Richard E Turner

NeurIPS 2015 Parallel Predictive Entropy Search for Batch Global Optimization of Expensive Objective Functions Amar Shah, Zoubin Ghahramani

NeurIPS 2015 Particle Gibbs for Infinite Hidden Markov Models Nilesh Tripuraneni, Shixiang Gu, Hong Ge, Zoubin Ghahramani

ICML 2015 Predictive Entropy Search for Bayesian Optimization with Unknown Constraints Jose Miguel Hernandez-Lobato, Michael Gelbart, Matthew Hoffman, Ryan Adams, Zoubin Ghahramani

AISTATS 2015 Scalable Variational Gaussian Process Classification James Hensman, Alexander G. de G. Matthews, Zoubin Ghahramani

NeurIPS 2015 Statistical Model Criticism Using Kernel Two Sample Tests James R Lloyd, Zoubin Ghahramani

UAI 2015 Training Generative Neural Networks via Maximum Mean Discrepancy Optimization Gintare Karolina Dziugaite, Daniel M. Roy, Zoubin Ghahramani

AISTATS 2014 A Non-Parametric Conditional Factor Regression Model for Multi-Dimensional Input and Response Ava Bargi, Richard Yi Da Xu, Zoubin Ghahramani, Massimo Piccardi

ICML 2014 A Reversible Infinite HMM Using Normalised Random Measures David Knowles, Zoubin Ghahramani, Konstantina Palla

AAAI 2014 Automatic Construction and Natural-Language Description of Nonparametric Regression Models James Robert Lloyd, David Duvenaud, Roger B. Grosse, Joshua B. Tenenbaum, Zoubin Ghahramani

AISTATS 2014 Avoiding Pathologies in Very Deep Networks David Duvenaud, Oren Rippel, Ryan P. Adams, Zoubin Ghahramani

ICML 2014 Beta Diffusion Trees Creighton Heaukulani, David Knowles, Zoubin Ghahramani

ICML 2014 Cold-Start Active Learning with Robust Ordinal Matrix Factorization Neil Houlsby, Jose Miguel Hernandez-Lobato, Zoubin Ghahramani

NeurIPS 2014 Gaussian Process Volatility Model Yue Wu, José Miguel Hernández-Lobato, Zoubin Ghahramani

NeurIPS 2014 General Table Completion Using a Bayesian Nonparametric Model Isabel Valera, Zoubin Ghahramani

ICML 2014 Pitfalls in the Use of Parallel Inference for the Dirichlet Process Yarin Gal, Zoubin Ghahramani

NeurIPS 2014 Predictive Entropy Search for Efficient Global Optimization of Black-Box Functions José Miguel Hernández-Lobato, Matthew W Hoffman, Zoubin Ghahramani

ICML 2014 Probabilistic Matrix Factorization with Non-Random Missing Data Jose Miguel Hernandez-Lobato, Neil Houlsby, Zoubin Ghahramani

ICML 2014 Randomized Nonlinear Component Analysis David Lopez-Paz, Suvrit Sra, Alex Smola, Zoubin Ghahramani, Bernhard Schoelkopf

ICML 2014 Scalable Gaussian Process Structured Prediction for Grid Factor Graph Applications Sebastien Bratieres, Novi Quadrianto, Sebastian Nowozin, Zoubin Ghahramani

ICML 2014 Stochastic Inference for Scalable Probabilistic Modeling of Binary Matrices Jose Miguel Hernandez-Lobato, Neil Houlsby, Zoubin Ghahramani

AISTATS 2014 Student-T Processes as Alternatives to Gaussian Processes Amar Shah, Andrew Gordon Wilson, Zoubin Ghahramani

AISTATS 2013 Active Learning for Interactive Visualization Tomoharu Iwata, Neil Houlsby, Zoubin Ghahramani

UAI 2013 Determinantal Clustering Processes - A Nonparametric Bayesian Approach to Kernel Based Semi-Supervised Clustering Amar Shah, Zoubin Ghahramani

ICML 2013 Dynamic Probabilistic Models for Latent Feature Propagation in Social Networks Creighton Heaukulani, Zoubin Ghahramani

UAI 2013 The Supervised IBP: Neighbourhood Preserving Infinite Latent Feature Models Novi Quadrianto, Viktoriia Sharmanska, David A. Knowles, Zoubin Ghahramani

ECML-PKDD 2013 Variational Hidden Conditional Random Fields with Coupled Dirichlet Process Mixtures Konstantinos Bousmalis, Stefanos Zafeiriou, Louis-Philippe Morency, Maja Pantic, Zoubin Ghahramani

UAI 2013 Warped Mixtures for Nonparametric Cluster Shapes Tomoharu Iwata, David Duvenaud, Zoubin Ghahramani

AISTATS 2012 A Nonparametric Bayesian Model for Multiple Clustering with Overlapping Feature Views Donglin Niu, Jennifer Dy, Zoubin Ghahramani

NeurIPS 2012 A Nonparametric Variable Clustering Model Konstantina Palla, Zoubin Ghahramani, David A. Knowles

NeurIPS 2012 Active Learning of Model Evidence Using Bayesian Quadrature Michael Osborne, Roman Garnett, Zoubin Ghahramani, David K. Duvenaud, Stephen J. Roberts, Carl E. Rasmussen

ICML 2012 An Infinite Latent Attribute Model for Network Data Konstantina Palla, David A. Knowles, Zoubin Ghahramani

AISTATS 2012 Bayesian Classifier Combination Hyun-Chul Kim, Zoubin Ghahramani

NeurIPS 2012 Collaborative Gaussian Processes for Preference Learning Neil Houlsby, Ferenc Huszar, Zoubin Ghahramani, Jose M. Hernández-lobato

NeurIPS 2012 Continuous Relaxations for Discrete Hamiltonian Monte Carlo Yichuan Zhang, Zoubin Ghahramani, Amos J. Storkey, Charles A. Sutton

ICML 2012 Copula-Based Kernel Dependency Measures Barnabás Póczos, Zoubin Ghahramani, Jeff G. Schneider

ICML 2012 Evaluating Bayesian and L1 Approaches for Sparse Unsupervised Learning Shakir Mohamed, Katherine A. Heller, Zoubin Ghahramani

AISTATS 2012 Flexible Martingale Priors for Deep Hierarchies Jacob Steinhardt, Zoubin Ghahramani

ICML 2012 Gaussian Process Regression Networks Andrew Gordon Wilson, David A. Knowles, Zoubin Ghahramani

AISTATS 2012 Gaussian Processes for Time-Marked Time-Series Data John Cunningham, Zoubin Ghahramani, Carl Rasmussen

ECML-PKDD 2012 Modelling Input Varying Correlations Between Multiple Responses Andrew Gordon Wilson, Zoubin Ghahramani

NeurIPS 2012 Random Function Priors for Exchangeable Arrays with Applications to Graphs and Relational Data James Lloyd, Peter Orbanz, Zoubin Ghahramani, Daniel M. Roy

AISTATS 2011 Approximate Inference for the Loss-Calibrated Bayesian Simon Lacoste–Julien, Ferenc Huszár, Zoubin Ghahramani

UAI 2011 Generalised Wishart Processes Andrew Gordon Wilson, Zoubin Ghahramani

ICML 2011 Message Passing Algorithms for the Dirichlet Diffusion Tree David A. Knowles, Jurgen Van Gael, Zoubin Ghahramani

UAI 2011 Pitman-Yor Diffusion Trees David A. Knowles, Zoubin Ghahramani

NeurIPS 2011 Testing a Bayesian Measure of Representativeness Using a Large Image Database Joshua T. Abbott, Katherine A. Heller, Zoubin Ghahramani, Thomas L. Griffiths

JMLR 2011 The Indian Buffet Process: An Introduction and Review Thomas L. Griffiths, Zoubin Ghahramani

NeurIPS 2010 Copula Processes Andrew G Wilson, Zoubin Ghahramani

AISTATS 2010 Dependent Indian Buffet Processes Sinead Williamson, Peter Orbanz, Zoubin Ghahramani

JMLR 2010 Kronecker Graphs: An Approach to Modeling Networks Jure Leskovec, Deepayan Chakrabarti, Jon Kleinberg, Christos Faloutsos, Zoubin Ghahramani

AISTATS 2010 Learning the Structure of Deep Sparse Graphical Models Ryan P. Adams, Hanna Wallach, Zoubin Ghahramani

NeurIPS 2010 Tree-Structured Stick Breaking for Hierarchical Data Zoubin Ghahramani, Michael I. Jordan, Ryan P. Adams

AISTATS 2009 A Kernel Method for Unsupervised Structured Network Inference Christoph Lippert, Oliver Stegle, Zoubin Ghahramani, Karsten Borgwardt

ICML 2009 Accelerated Sampling for the Indian Buffet Process Finale Doshi-Velez, Zoubin Ghahramani

ICML 2009 Archipelago: Nonparametric Bayesian Semi-Supervised Learning Ryan Prescott Adams, Zoubin Ghahramani

AISTATS 2009 Choosing a Variable to Clamp Frederik Eaton, Zoubin Ghahramani

UAI 2009 Correlated Non-Parametric Latent Feature Models Finale Doshi-Velez, Zoubin Ghahramani

AISTATS 2009 Factorial Mixture of Gaussians and the Marginal Independence Model Ricardo Silva, Zoubin Ghahramani

NeurIPS 2009 Large Scale Nonparametric Bayesian Inference: Data Parallelisation in the Indian Buffet Process Finale Doshi-velez, Shakir Mohamed, Zoubin Ghahramani, David A. Knowles

AISTATS 2009 Probabilistic Models for Incomplete Multi-Dimensional Arrays Wei Chu, Zoubin Ghahramani

AISTATS 2009 The Block Diagonal Infinite Hidden Markov Model Thomas Stepleton, Zoubin Ghahramani, Geoffrey Gordon, Tai-Sing Lee

JMLR 2009 The Hidden Life of Latent Variables: Bayesian Learning with Mixed Graph Models Ricardo Silva, Zoubin Ghahramani

AISTATS 2009 Tree-Based Inference for Dirichlet Process Mixtures Yang Xu, Katherine Heller, Zoubin Ghahramani

NeurIPS 2008 Bayesian Exponential Family PCA Shakir Mohamed, Zoubin Ghahramani, Katherine A. Heller

ICML 2008 Beam Sampling for the Infinite Hidden Markov Model Jurgen Van Gael, Yunus Saatci, Yee Whye Teh, Zoubin Ghahramani

MLJ 2008 Flexible Latent Variable Models for Multi-Task Learning Jian Zhang, Zoubin Ghahramani, Yiming Yang

ICML 2008 Statistical Models for Partial Membership Katherine A. Heller, Sinead Williamson, Zoubin Ghahramani

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

AISTATS 2007 A Nonparametric Bayesian Approach to Modeling Overlapping Clusters Katherine A. Heller, Zoubin Ghahramani

AISTATS 2007 Analogical Reasoning with Relational Bayesian Sets Ricardo Silva, Katherine A. Heller, Zoubin Ghahramani

NeurIPS 2007 Hidden Common Cause Relations in Relational Learning Ricardo Silva, Wei Chu, Zoubin Ghahramani

AISTATS 2007 Local and Global Sparse Gaussian Process Approximations Edward Snelson, Zoubin Ghahramani

ICML 2007 Machine Learning, Proceedings of the Twenty-Fourth International Conference (ICML 2007), Corvallis, Oregon, USA, June 20-24, 2007 Zoubin Ghahramani

AISTATS 2007 Stick-Breaking Construction for the Indian Buffet Process Yee Whye Teh, Dilan Grür, Zoubin Ghahramani

ICML 2006 A New Approach to Data Driven Clustering Arik Azran, Zoubin Ghahramani

UAI 2006 A Non-Parametric Bayesian Method for Inferring Hidden Causes Frank D. Wood, Thomas L. Griffiths, Zoubin Ghahramani

CVPR 2006 A Simple Bayesian Framework for Content-Based Image Retrieval Katherine A. Heller, Zoubin Ghahramani

UAI 2006 Bayesian Inference for Gaussian Mixed Graph Models Ricardo Bezerra de Andrade e Silva, Zoubin Ghahramani

UAI 2006 MCMC for Doubly-Intractable Distributions Iain Murray, Zoubin Ghahramani, David J. C. MacKay

NeurIPS 2006 Modeling Dyadic Data with Binary Latent Factors Edward Meeds, Zoubin Ghahramani, Radford M. Neal, Sam T. Roweis

NeurIPS 2006 Relational Learning with Gaussian Processes Wei Chu, Vikas Sindhwani, Zoubin Ghahramani, S. S. Keerthi

CVPR 2006 Spectral Methods for Automatic Multiscale Data Clustering Arik Azran, Zoubin Ghahramani

UAI 2006 Variable Noise and Dimensionality Reduction for Sparse Gaussian Processes Edward Lloyd Snelson, Zoubin Ghahramani

ICML 2005 Bayesian Hierarchical Clustering Katherine A. Heller, Zoubin Ghahramani

NeurIPS 2005 Bayesian Sets Zoubin Ghahramani, Katherine A. Heller

ICML 2005 Compact Approximations to Bayesian Predictive Distributions Edward Lloyd Snelson, Zoubin Ghahramani

AISTATS 2005 Frontmatter and Preface Robert G. Cowell, Zoubin Ghahramani

JMLR 2005 Gaussian Processes for Ordinal Regression Wei Chu, Zoubin Ghahramani

NeurIPS 2005 Infinite Latent Feature Models and the Indian Buffet Process Zoubin Ghahramani, Thomas L. Griffiths

NeurIPS 2005 Learning Multiple Related Tasks Using Latent Independent Component Analysis Jian Zhang, Zoubin Ghahramani, Yiming Yang

NeurIPS 2005 Nested Sampling for Potts Models Iain Murray, David MacKay, Zoubin Ghahramani, John Skilling

ICML 2005 Preference Learning with Gaussian Processes Wei Chu, Zoubin Ghahramani

NeurIPS 2005 Sparse Gaussian Processes Using Pseudo-Inputs Edward Snelson, Zoubin Ghahramani

ECML-PKDD 2005 U-Likelihood and U-Updating Algorithms: Statistical Inference in Latent Variable Models JaeMo Sung, Sung Yang Bang, Seungjin Choi, Zoubin Ghahramani

ICML 2004 A Graphical Model for Protein Secondary Structure Prediction Wei Chu, Zoubin Ghahramani, David L. Wild

NeurIPS 2004 A Probabilistic Model for Online Document Clustering with Application to Novelty Detection Jian Zhang, Zoubin Ghahramani, Yiming Yang

UAI 2004 Bayesian Learning in Undirected Graphical Models: Approximate MCMC Algorithms Iain Murray, Zoubin Ghahramani

NeurIPS 2004 Nonparametric Transforms of Graph Kernels for Semi-Supervised Learning Xiaojin Zhu, Jaz Kandola, Zoubin Ghahramani, John D. Lafferty

ICML 2004 Predictive Automatic Relevance Determination by Expectation Propagation Yuan (Alan) Qi, Thomas P. Minka, Rosalind W. Picard, Zoubin Ghahramani

UAI 2003 On the Convergence of Bound Optimization Algorithms Ruslan Salakhutdinov, Sam T. Roweis, Zoubin Ghahramani

ICML 2003 Optimization with EM and Expectation-Conjugate-Gradient Ruslan Salakhutdinov, Sam T. Roweis, Zoubin Ghahramani

ICML 2003 Semi-Supervised Learning Using Gaussian Fields and Harmonic Functions Xiaojin Zhu, Zoubin Ghahramani, John D. Lafferty

NeurIPS 2003 Warped Gaussian Processes Edward Snelson, Zoubin Ghahramani, Carl E. Rasmussen

NeurIPS 2002 Bayesian Monte Carlo Zoubin Ghahramani, Carl E. Rasmussen

NeurIPS 2002 Learning with Multiple Labels Rong Jin, Zoubin Ghahramani

NeurIPS 2001 Infinite Mixtures of Gaussian Process Experts Carl E. Rasmussen, Zoubin Ghahramani

NeurIPS 2001 The Infinite Hidden Markov Model Matthew J. Beal, Zoubin Ghahramani, Carl E. Rasmussen

NeurIPS 2000 Occam's Razor Carl Edward Rasmussen, Zoubin Ghahramani

NeurIPS 2000 Propagation Algorithms for Variational Bayesian Learning Zoubin Ghahramani, Matthew J. Beal

NeCo 2000 SMEM Algorithm for Mixture Models Naonori Ueda, Ryohei Nakano, Zoubin Ghahramani, Geoffrey E. Hinton

NeCo 2000 Variational Learning for Switching State-Space Models Zoubin Ghahramani, Geoffrey E. Hinton

NeCo 1999 A Unifying Review of Linear Gaussian Models Sam T. Roweis, Zoubin Ghahramani

MLJ 1999 An Introduction to Variational Methods for Graphical Models Michael I. Jordan, Zoubin Ghahramani, Tommi S. Jaakkola, Lawrence K. Saul

NeurIPS 1999 Learning to Parse Images Geoffrey E. Hinton, Zoubin Ghahramani, Yee Whye Teh

NeurIPS 1999 Variational Inference for Bayesian Mixtures of Factor Analysers Zoubin Ghahramani, Matthew J. Beal

NeurIPS 1998 Learning Nonlinear Dynamical Systems Using an EM Algorithm Zoubin Ghahramani, Sam T. Roweis

NeurIPS 1998 SMEM Algorithm for Mixture Models Naonori Ueda, Ryohei Nakano, Zoubin Ghahramani, Geoffrey E. Hinton

MLJ 1997 Factorial Hidden Markov Models Zoubin Ghahramani, Michael I. Jordan

NeurIPS 1997 Hierarchical Non-Linear Factor Analysis and Topographic Maps Zoubin Ghahramani, Geoffrey E. Hinton

JAIR 1996 Active Learning with Statistical Models David A. Cohn, Zoubin Ghahramani, Michael I. Jordan

NeurIPS 1996 Hidden Markov Decision Trees Michael I. Jordan, Zoubin Ghahramani, Lawrence K. Saul

NeurIPS 1995 Factorial Hidden Markov Models Zoubin Ghahramani, Michael I. Jordan

NeurIPS 1994 Active Learning with Statistical Models David A. Cohn, Zoubin Ghahramani, Michael I. Jordan

NeurIPS 1994 Computational Structure of Coordinate Transformations: A Generalization Study Zoubin Ghahramani, Daniel M. Wolpert, Michael I. Jordan

NeurIPS 1994 Factorial Learning and the EM Algorithm Zoubin Ghahramani

NeurIPS 1994 Forward Dynamic Models in Human Motor Control: Psychophysical Evidence Daniel M. Wolpert, Zoubin Ghahramani, Michael I. Jordan

NeurIPS 1993 Supervised Learning from Incomplete Data via an EM Approach Zoubin Ghahramani, Michael I. Jordan