Zoubin Ghahramani

发表

Testing a Bayesian Measure of Representativeness Using a Large Image Database

Thomas L. Griffiths, Joshua T. Abbott, Katherine A. Heller, 2011, NIPS.

Bayesian Classifier Combination

Hyun-Chul Kim, Zoubin Ghahramani, Zoubin Ghahramani, 2012, AISTATS.

A study of the effect of JPG compression on adversarial images pdf

Zoubin Ghahramani, Gintare Karolina Dziugaite, Daniel M. Roy, 2016, ArXiv.

MCMC parameter learning in spatial statistics

Zoubin Ghahramani, Iain Murray, Djc MacKay, 2006 .

Archipelago: nonparametric Bayesian semi-supervised learning

Ryan P. Adams, Zoubin Ghahramani, Zoubin Ghahramani, 2009, ICML '09.

Are arm trajectories planned in kinematic or dynamic coordinates? An adaptation study

Michael I. Jordan, Zoubin Ghahramani, Daniel M. Wolpert, 1995, Experimental Brain Research.

Lost Relatives of the Gumbel Trick

Zoubin Ghahramani, Matej Balog, Nilesh Tripuraneni, 2017, ICML.

Computational principles of multisensory integration: studies of adaptation to novel visuo-auditory remappings

Michael I. Jordan, Zoubin Ghahramani, Daniel M. Wolpert, 1995 .

Unsupervised learning of sensory-motor primitives

Zoubin Ghahramani, Emanuel Todorov, E. Todorov, 2003, Proceedings of the 25th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (IEEE Cat. No.03CH37439).

Switching State-Space Models

Geoffrey E. Hinton, Zoubin Ghahramani, Zoubin Ghahramani, 1996 .

Learning from Incomplete Data

Michael I. Jordan, Zoubin Ghahramani, Zoubin Ghahramani, 1994 .

Biomarker discovery in microarray gene expression data with Gaussian processes

Wei Chu, Zoubin Ghahramani, Francesco Falciani, 2005, Bioinform..

Denotational validation of higher-order Bayesian inference

Ohad Kammar, Hongseok Yang, Zoubin Ghahramani, 2017, Proc. ACM Program. Lang..

A Probabilistic Model for Dirty Multi-task Feature Selection

Daniel Hernández-Lobato, Zoubin Ghahramani, José Miguel Hernández-Lobato, 2015, ICML.

Zoubin Ghahramani, Finale Doshi-Velez, Zoubin Ghahramani, 2009, UAI.

Temporal processing with connectionist networks

Zoubin Ghahramani, R. B. Allen, R. Allen, 1991, IJCNN-91-Seattle International Joint Conference on Neural Networks.

Predictive automatic relevance determination by expectation propagation

Yuan Qi, Zoubin Ghahramani, Tom Minka, 2004, ICML.

A Non-Parametric Bayesian Method for Inferring Hidden Causes pdf

Thomas L. Griffiths, Frank D. Wood, Zoubin Ghahramani, 2006, UAI.

Cold-start Active Learning with Robust Ordinal Matrix Factorization

Zoubin Ghahramani, José Miguel Hernández-Lobato, Neil Houlsby, 2014, ICML.

The variational Kalman smoother

Zoubin Ghahramani, Matthew J. Beal, Zoubin Ghahramani, 2001 .

Bayesian Active Learning for Classification and Preference Learning pdf

Zoubin Ghahramani, Neil Houlsby, Máté Lengyel, 2011, ArXiv.

Unsupervised Learning

Zoubin Ghahramani, Zoubin Ghahramani, 2003, Advanced Lectures on Machine Learning.

Introduction of New Associate Editors

Jiri Matas, Zoubin Ghahramani, Ramin Zabih, 2008, IEEE Trans. Pattern Anal. Mach. Intell..

A Robust Bayesian Two-Sample Test for Detecting Intervals of Differential Gene Expression in Microarray Time Series

Zoubin Ghahramani, Oliver Stegle, Karsten M. Borgwardt, 2009, RECOMB.

The Hidden Life of Latent Variables: Bayesian Learning with Mixed Graph Models

Zoubin Ghahramani, Ricardo Bezerra de Andrade e Silva, Zoubin Ghahramani, 2009, J. Mach. Learn. Res..

Determinantal clustering process - a nonparametric Bayesian approach to kernel based semi-supervised clustering

Zoubin Ghahramani, Amar Shah, Zoubin Ghahramani, 2013, UAI 2013.

Random Sum-Product Networks: A Simple and Effective Approach to Probabilistic Deep Learning

Kristian Kersting, Robert Peharz, Zoubin Ghahramani, 2019, UAI.

MetaGAN: An Adversarial Approach to Few-Shot Learning

Yoshua Bengio, Zoubin Ghahramani, Yangqiu Song, 2018, NeurIPS.

Mixture models for learning from incomplete data

Michael I. Jordan, Zoubin Ghahramani, Zoubin Ghahramani, 1997, COLT 1997.

Scalable Discrete Sampling as a Multi-Armed Bandit Problem

Zoubin Ghahramani, Yutian Chen, Zoubin Ghahramani, 2015, ICML.

A Generative Model of Vector Space Semantics

Jacob Andreas, Zoubin Ghahramani, Zoubin Ghahramani, 2013, CVSM@ACL.

Scalable Gaussian Process Structured Prediction for Grid Factor Graph Applications

Sebastian Nowozin, Zoubin Ghahramani, Novi Quadrianto, 2014, ICML.

Nonparametric Bayesian Sparse Factor Models with application to Gene Expression modelling pdf

Zoubin Ghahramani, David A. Knowles, Zoubin Ghahramani, 2010, The Annals of Applied Statistics.

AdvancedHMC.jl: A robust, modular and e cient implementation of advanced HMC algorithms

Kai Xu, Zoubin Ghahramani, Will Tebbutt, 2019, AABI.

Bayesian Methods for Unsupervised Learning

Zoubin Ghahramani, Zoubin Ghahramani, 2003 .

Branch-recombinant Gaussian processes for analysis of perturbations in biological time series

Zoubin Ghahramani, Christopher A. Penfold, Lorenz Wernisch, 2018, bioRxiv.

An Introduction to Variational Methods for Graphical Models

Michael I. Jordan, Tommi S. Jaakkola, Zoubin Ghahramani, 1999, Machine-mediated learning.

MCMC for Doubly-intractable Distributions

Zoubin Ghahramani, Iain Murray, David J. C. MacKay, 2006, UAI.

A nonparametric variable clustering model

Zoubin Ghahramani, David A. Knowles, Konstantina Palla, 2012, NIPS.

Magnetic Hamiltonian Monte Carlo

Richard E. Turner, Zoubin Ghahramani, Nilesh Tripuraneni, 2016, ICML.

Outlier Robust Learning Algorithm for Gaussian Process Classification

김현철, Zoubin Ghahramani, Zoubin Ghahramani, 2007 .

Sublinear Approximate Inference for Probabilistic Programs

Zoubin Ghahramani, Yutian Chen, Vikash K. Mansinghka, 2014 .

Learning Multiple Related Tasks using Latent Independent Component Analysis

Yiming Yang, Zoubin Ghahramani, Jian Zhang, 2005, NIPS.

Randomized algorithms for fast Bayesian hierarchical clustering

Katherine A. Heller, Zoubin Ghahramani, Zoubin Ghahramani, 2005 .

Sparse Gaussian Processes using Pseudo-inputs

Zoubin Ghahramani, Edward Snelson, Zoubin Ghahramani, 2005, NIPS.

Large Scale Nonparametric Bayesian Inference: Data Parallelisation in the Indian Buffet Process

Zoubin Ghahramani, Finale Doshi-Velez, David A. Knowles, 2009, NIPS.

Improving Output Uncertainty Estimation and Generalization in Deep Learning via Neural Network Gaussian Processes

Tomoharu Iwata, Zoubin Ghahramani, Zoubin Ghahramani, 2017, 1707.05922.

Time for bayes: comments to Amari and Kohonen

Zoubin Ghahramani, Zoubin Ghahramani, 1999 .

Efficient and Robust Machine Learning for Real-World Systems pdf

Holger Fröning, Sebastian Tschiatschek, Franz Pernkopf, 2018, ArXiv.

Editor’s Note

Jiri Matas, Zoubin Ghahramani, Ramin Zabih, 2010, IEEE Transactions on Pattern Analysis and Machine Intelligence.

General Latent Feature Models for Heterogeneous Datasets

Zoubin Ghahramani, Isabel Valera, Melanie F. Pradier, 2017, J. Mach. Learn. Res..

Towards semi-supervised classification with Markov random fields

Zoubin Ghahramani, Xiaojin Zhu, John Lafferty, 2002 .

The Supervised IBP: Neighbourhood Preserving Infinite Latent Feature Models pdf

Zoubin Ghahramani, David A. Knowles, Novi Quadrianto, 2013, UAI.

Spectral Methods for Automatic Multiscale Data Clustering

Zoubin Ghahramani, Arik Azran, Zoubin Ghahramani, 2006, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06).

Probabilistic graphical models for semi-supervised traffic classification

Zoubin Ghahramani, Andrew W. Moore, Jurgen Van Gael, 2010, IWCMC.

Dynamic Covariance Models for Multivariate Financial Time Series

Zoubin Ghahramani, José Miguel Hernández-Lobato, Yue Wu, 2013, ICML.

Distributed Inference for Dirichlet Process Mixture Models

Zoubin Ghahramani, Yutian Chen, Hong Ge, 2015, ICML.

Model Reductions for Inference: Generality of Pairwise, Binary, and Planar Factor Graphs

Zoubin Ghahramani, Frederik Eaton, Zoubin Ghahramani, 2013, Neural Computation.

Training generative neural networks via Maximum Mean Discrepancy optimization

Zoubin Ghahramani, Gintare Karolina Dziugaite, Daniel M. Roy, 2015, UAI.

Beta Diffusion Trees

Zoubin Ghahramani, David A. Knowles, Creighton Heaukulani, 2014, ICML.

MCMC for Variationally Sparse Gaussian Processes

James Hensman, Zoubin Ghahramani, Maurizio Filippone, 2015, NIPS.

Learning from labeled and unlabeled data with label propagation

Zoubin Ghahramani, Xiaojin Zhu, Xiaojin Zhu, 2002 .

The Status of Structural Genomics Defined Through the Analysis of Current Targets and Structures

Tong Liu, Li Chen, Philip E. Bourne, 2003, Pacific Symposium on Biocomputing.

Motor learning models

Zoubin Ghahramani, Daniel M. Wolpert, Zoubin Ghahramani, 2006 .

The Automatic Statistician

Zoubin Ghahramani, David Janz, Emma Smith, 2019, Automated Machine Learning.

Pareto Frontier Learning with Expensive Correlated Objectives

Zoubin Ghahramani, Amar Shah, Zoubin Ghahramani, 2016, ICML.

Probabilistic machine learning and artificial intelligence

Zoubin Ghahramani, Zoubin Ghahramani, 2015, Nature.

Baysian Segmental Models for Protein Secondary Structure and Contact Map Prediction

Wei Chu, Zoubin Ghahramani, Alexei A. Podtelezhnikov, 2006 .

Active Learning of Model Evidence Using Bayesian Quadrature

Carl E. Rasmussen, Roman Garnett, Zoubin Ghahramani, 2012, NIPS.

Solving inverse problems using an EM approach to density estimation

Zoubin Ghahramani, Zoubin Ghahramani, 1993 .

Dropout as a Bayesian Approximation: Appendix

Zoubin Ghahramani, Yarin Gal, Zoubin Ghahramani, 2015, 1506.02157.

MFDTs: mean field dynamic trees

Zoubin Ghahramani, Christopher K. I. Williams, Amos J. Storkey, 2000, Proceedings 15th International Conference on Pattern Recognition. ICPR-2000.

Expectation Propagation for Infinite Mixtures

Zoubin Ghahramani, Thomas P. Minka, T. Minka, 2017 .

Sandwiching the marginal likelihood using bidirectional Monte Carlo pdf

Ryan P. Adams, Zoubin Ghahramani, Roger B. Grosse, 2015, ArXiv.

A neural network for learning how to parse tree adjoining grammars

Zoubin Ghahramani, Zoubin Ghahramani, 1990 .

Bayesian Sets

Katherine A. Heller, Zoubin Ghahramani, Zoubin Ghahramani, 2005, NIPS.

Accelerated sampling for the Indian Buffet Process

Zoubin Ghahramani, Finale Doshi-Velez, Zoubin Ghahramani, 2009, ICML '09.

SIGMa: simple greedy matching for aligning large knowledge bases

Gjergji Kasneci, Zoubin Ghahramani, Thore Graepel, 2012, KDD.

Beam sampling for the infinite hidden Markov model

Yee Whye Teh, Zoubin Ghahramani, Yunus Saatci, 2008, ICML '08.

Gaussian Process Regression Networks

Andrew Gordon Wilson, Zoubin Ghahramani, David A. Knowles, 2011, ICML.

Latent-Space Variational Bayes

Zoubin Ghahramani, Sung Yang Bang, JaeMo Sung, 2008, IEEE Transactions on Pattern Analysis and Machine Intelligence.

Clustering Protein Sequence and Structure Space with Infinite Gaussian Mixture Models

Carl E. Rasmussen, Zoubin Ghahramani, David L. Wild, 2003, Pacific Symposium on Biocomputing.

Stochastic Inference for Scalable Probabilistic Modeling of Binary Matrices

Zoubin Ghahramani, José Miguel Hernández-Lobato, Neil Houlsby, 2014, ICML.

Simultaneous and Mapping With Sparse Extended Information

Zoubin Ghahramani, Andrew Y. Ng, Sebastian Thrun, 2014 .

Dynamic Probabilistic Models for Latent Feature Propagation in Social Networks

Zoubin Ghahramani, Creighton Heaukulani, Zoubin Ghahramani, 2013, ICML.

SMEM Algorithm for Mixture Models

Geoffrey E. Hinton, Naonori Ueda, Zoubin Ghahramani, 1998, Neural Computation.

Adaptation to switching force fields

Zoubin Ghahramani, At Korenberg, Zoubin Ghahramani, 2001 .

A theory of optimal motor-sensory primitives

Zoubin Ghahramani, Emanuel Todorov, E. Todorov, 2001 .

Learning Continuous Treatment Policy and Bipartite Embeddings for Matching with Heterogeneous Causal Effects pdf

Zoubin Ghahramani, Mingshi Wang, Will Y. Zou, 2020, ArXiv.

Adaptative feedback control for non-stationary dynamics

Zoubin Ghahramani, At Korenberg, Zoubin Ghahramani, 2001 .

Gaussian Process Vine Copulas for Multivariate Dependence

Zoubin Ghahramani, David Lopez-Paz, José Miguel Hernández-Lobato, 2013, ICML.

Determinantal Clustering Processes - A Nonparametric Bayesian Approach to Kernel Based Semi-Supervised Clustering pdf

Zoubin Ghahramani, Amar Shah, Zoubin Ghahramani, 2013, UAI.

Bayesian and L$_\mathbf{1}$ Approaches to Sparse Unsupervised Learning

Katherine A. Heller, Zoubin Ghahramani, Shakir Mohamed, 2011 .

Continuous Relaxations for Discrete Hamiltonian Monte Carlo

Yichuan Zhang, Zoubin Ghahramani, Charles A. Sutton, 2012, NIPS.

Graphical models: parameter learning

Zoubin Ghahramani, Zoubin Ghahramani, 2002 .

Predictive Entropy Search for Efficient Global Optimization of Black-box Functions

Matthew W. Hoffman, Zoubin Ghahramani, José Miguel Hernández-Lobato, 2014, NIPS.

A Bayesian network model for protein fold and remote homologue recognition

Zoubin Ghahramani, David L. Wild, A. Raval, 2002, Bioinform..

Hidden Common Cause Relations in Relational Learning

Wei Chu, Zoubin Ghahramani, Ricardo Bezerra de Andrade e Silva, 2007, NIPS.

A Theoretically Grounded Application of Dropout in Recurrent Neural Networks

Zoubin Ghahramani, Yarin Gal, Zoubin Ghahramani, 2015, NIPS.

Variable Noise and Dimensionality Reduction for Sparse Gaussian processes pdf

Zoubin Ghahramani, Edward Snelson, Zoubin Ghahramani, 2006, UAI.

Bayesian and L1 Approaches to Sparse Unsupervised Learning pdf

Katherine A. Heller, Zoubin Ghahramani, Shakir Mohamed, 2011, ICML 2012.

Student-t Processes as Alternatives to Gaussian Processes

Andrew Gordon Wilson, Zoubin Ghahramani, Amar Shah, 2014, AISTATS.

Identifying Protein Complexes in High-Throughput Protein Interaction Screens Using an Infinite Latent Feature Model

Wei Chu, Zoubin Ghahramani, David L. Wild, 2005, Pacific Symposium on Biocomputing.

Imitation networks: Few-shot learning of neural networks from scratch pdf

Koh Takeuchi, Naonori Ueda, Tomoharu Iwata, 2018, ArXiv.

Hidden Markov Decision Trees

Michael I. Jordan, Zoubin Ghahramani, Lawrence K. Saul, 1996, NIPS.

Protein secondary structure prediction using sigmoid belief networks to parameterize segmental semi-Markov models

Wei Chu, Zoubin Ghahramani, David L. Wild, 2004, ESANN.

Appearance-based gender classification with Gaussian processes

Hyun-Chul Kim, Zoubin Ghahramani, Daijin Kim, 2006, Pattern Recognit. Lett..

A Hierarchical Community of Experts

Brian Sallans, Zoubin Ghahramani, Geoffrey E. Hinton, 1999, Learning in Graphical Models.

Introduction of New Associate Editors

David J. Fleet, David J. Kriegman, Zoubin Ghahramani, 2008, IEEE Trans. Pattern Anal. Mach. Intell..

Probabilistic Matrix Factorization with Non-random Missing Data

Zoubin Ghahramani, José Miguel Hernández-Lobato, Neil Houlsby, 2014, ICML.

Propagation Algorithms for Variational Bayesian Learning

Zoubin Ghahramani, Matthew J. Beal, Zoubin Ghahramani, 2000, NIPS.

A General Framework for Constrained Bayesian Optimization using Information-based Search

Matthew W. Hoffman, Ryan P. Adams, Zoubin Ghahramani, 2015, J. Mach. Learn. Res..

Markov Beta Processes for Time Evolving Dictionary Learning

Zoubin Ghahramani, Amar Shah, Zoubin Ghahramani, 2016, UAI.

Probabilistic Deep Learning using Random Sum-Product Networks pdf

Kristian Kersting, Robert Peharz, Zoubin Ghahramani, 2018, ArXiv.

R/BHC: fast Bayesian hierarchical clustering for microarray data

Yang Xu, Katherine A. Heller, Zoubin Ghahramani, 2009, BMC Bioinformatics.

Bayesian hierarchical clustering

Katherine A. Heller, Zoubin Ghahramani, Zoubin Ghahramani, 2005, ICML.

Outlier Robust Gaussian Process Classification

Hyun-Chul Kim, Zoubin Ghahramani, Zoubin Ghahramani, 2008, SSPR/SPR.

Pitman-Yor Diffusion Trees

Zoubin Ghahramani, David A. Knowles, Zoubin Ghahramani, 2011, UAI.

Scalable Variational Gaussian Process Classification

James Hensman, Zoubin Ghahramani, Alexander G. de G. Matthews, 2014, AISTATS.

Multiple linear controllers for nonlinear and nonstationary dynamics

Zoubin Ghahramani, Daniel M. Wolpert, Philipp Vetter, 2000 .

Variational Hidden Conditional Random Fields with Coupled Dirichlet Process Mixtures

Stefanos Zafeiriou, Maja Pantic, Zoubin Ghahramani, 2013, ECML/PKDD.

Particle Gibbs for Infinite Hidden Markov Models

Zoubin Ghahramani, Nilesh Tripuraneni, Hong Ge, 2015, NIPS.

Evaluating Bayesian and L1 Approaches for Sparse Unsupervised Learning

Katherine A. Heller, Zoubin Ghahramani, Shakir Mohamed, 2011, ICML.

Factorial Hidden Markov Models

Michael I. Jordan, Zoubin Ghahramani, Zoubin Ghahramani, 1995, Machine Learning.

Tree-Based Inference for Dirichlet Process Mixtures

Yang Xu, Katherine A. Heller, Zoubin Ghahramani, 2009, AISTATS.

Scaling the iHMM: Parallelization versus Hadoop

Zoubin Ghahramani, Andreas Vlachos, Jurgen Van Gael, 2010, 2010 10th IEEE International Conference on Computer and Information Technology.

A Simple and General Exponential Family Framework for Partial Membership and Factor Analysis

Edoardo M. Airoldi, Stephen E. Fienberg, Katherine A. Heller, 2014 .

On the Convergence of Bound Optimization Algorithms

Zoubin Ghahramani, Ruslan Salakhutdinov, Sam T. Roweis, 2002, UAI.

Introduction of New Associate Editors

David J. Fleet, David J. Kriegman, Zoubin Ghahramani, 2008, IEEE Trans. Pattern Anal. Mach. Intell..

Infinite Sparse Factor Analysis and Infinite Independent Components Analysis

Zoubin Ghahramani, David A. Knowles, Zoubin Ghahramani, 2007, ICA.

The Indian Buffet Process: An Introduction and Review

Thomas L. Griffiths, Zoubin Ghahramani, T. Griffiths, 2011, J. Mach. Learn. Res..

An Introduction to Hidden Markov Models and Bayesian Networks

Zoubin Ghahramani, Zoubin Ghahramani, 2001, Int. J. Pattern Recognit. Artif. Intell..

Metropolis Algorithms for Representative Subgraph Sampling

Hans-Peter Kriegel, Zoubin Ghahramani, Karsten M. Borgwardt, 2008, 2008 Eighth IEEE International Conference on Data Mining.

Einsum Networks: Fast and Scalable Learning of Tractable Probabilistic Circuits

Guy Van den Broeck, Kristian Kersting, Robert Peharz, 2020, ICML.

Probabilistic Meta-Representations Of Neural Networks pdf

Peter Dayan, Zoubin Ghahramani, Theofanis Karaletsos, 2018, ArXiv.

Kronecker Graphs: An Approach to Modeling Networks pdf

Christos Faloutsos, Jure Leskovec, Deepayan Chakrabarti, 2008, J. Mach. Learn. Res..

(Invited Talk) Bayesian Hidden Markov Models and Extensions

Zoubin Ghahramani, 2010, CoNLL.

Editor's Note

Jiri Matas, Zoubin Ghahramani, Ramin Zabih, 2010, IEEE Trans. Pattern Anal. Mach. Intell..

Split and Merge EM Algorithm for Improving Gaussian Mixture Density Estimates

Geoffrey E. Hinton, Naonori Ueda, Zoubin Ghahramani, 2000, J. VLSI Signal Process..

A Bayesian network approach to protein fold recognition

Zoubin Ghahramani, David L. Wild, Zoubin Ghahramani, 1998 .

Pitfalls in the use of Parallel Inference for the Dirichlet Process

Zoubin Ghahramani, Yarin Gal, Zoubin Ghahramani, 2014, ICML.

Infinite Mixtures of Gaussian Process Experts

Carl E. Rasmussen, Zoubin Ghahramani, Zoubin Ghahramani, 2001, NIPS.

Gaussian process regression with mismatched models

Thomas G. Dietterich, Zoubin Ghahramani, Suzanna Becker, 2002, Neural Information Processing Systems.

Q-Prop: Sample-Efficient Policy Gradient with An Off-Policy Critic pdf

Sergey Levine, Richard E. Turner, Zoubin Ghahramani, 2016, ICLR.

Parallel Predictive Entropy Search for Batch Global Optimization of Expensive Objective Functions

Zoubin Ghahramani, Amar Shah, Zoubin Ghahramani, 2015, NIPS.

Resource-Efficient Neural Networks for Embedded Systems pdf

Sebastian Tschiatschek, Franz Pernkopf, Robert Peharz, 2020, ArXiv.

Bayesian nonparametric latent feature models (with discussion)

Thomas L. Griffiths, Zoubin Ghahramani, Peter Sollich, 2006 .

Bayesian Generalised Ensemble Markov Chain Monte Carlo

Ole Winther, Zoubin Ghahramani, Jes Frellsen, 2016, AISTATS.

Bayesian Structured Prediction Using Gaussian Processes pdf

Zoubin Ghahramani, Novi Quadrianto, Sebastien Bratieres, 2013, ArXiv.

Bayesian model search for mixture models based on optimizing variational bounds

Naonori Ueda, Zoubin Ghahramani, Zoubin Ghahramani, 2002, Neural Networks.

Few-shot learning of neural networks from scratch by pseudo example optimization

Koh Takeuchi, Naonori Ueda, Tomoharu Iwata, 2018, BMVC.

Maps, Modules, and Internal Models in Human Motor Control

Zoubin Ghahramani, Daniel M. Wolpert, Zoubin Ghahramani, 2000 .

Nonparametric Probabilistic Modelling

Zoubin Ghahramani, Zoubin Ghahramani, 2012 .

Flexible Martingale Priors for Deep Hierarchies

Zoubin Ghahramani, Jacob Steinhardt, Zoubin Ghahramani, 2012, AISTATS.

Efficient Bayesian hierarchical clustering for gene expression data

Katherine A. Heller, Zoubin Ghahramani, Zoubin Ghahramani, 2006 .

Practical probabilistic programming with monads

Zoubin Ghahramani, Adam Ścibior, Andrew D. Gordon, 2015, Haskell.

Structure Discovery in Nonparametric Regression through Compositional Kernel Search pdf

Joshua B. Tenenbaum, Zoubin Ghahramani, Roger B. Grosse, 2013, ICML.

State of the Journal

Jiri Matas, Zoubin Ghahramani, Ramin Zabih, 2011, IEEE Trans. Pattern Anal. Mach. Intell..

Bayesian two-sample tests pdf

Zoubin Ghahramani, Karsten M. Borgwardt, Zoubin Ghahramani, 2009, ArXiv.

Factorial Mixture of Gaussians and the Marginal Independence Model

Zoubin Ghahramani, Ricardo Bezerra de Andrade e Silva, 2009, AISTATS.

Classical and Bayesian approaches to reconstructing genetic regulatory networks

Zoubin Ghahramani, Matthew J. Beal, Francesco Falciani, 2004 .

Editorial-State of the Transactions

David J. Fleet, David J. Kriegman, Zoubin Ghahramani, 2008, IEEE Trans. Pattern Anal. Mach. Intell..

Unsupervised Many-to-Many Object Matching for Relational Data

Tomoharu Iwata, Zoubin Ghahramani, James Robert Lloyd, 2016, IEEE Transactions on Pattern Analysis and Machine Intelligence.

Automatic Discovery of the Statistical Types of Variables in a Dataset

Zoubin Ghahramani, Isabel Valera, 2017, ICML.

GPstruct: Bayesian Structured Prediction Using Gaussian Processes

Zoubin Ghahramani, Novi Quadrianto, Sebastien Bratieres, 2015, IEEE Transactions on Pattern Analysis and Machine Intelligence.

Advances in neural information processing systems : proceedings of the ... conference

Thomas G. Dietterich, Richard P. Lippmann, Klaus-Robert Müller, 1989 .

An Introduction to Variational Methods for Graphical Models

Michael I. Jordan, Tommi S. Jaakkola, Zoubin Ghahramani, 1999, Machine Learning.

Relational Learning and Network Modelling Using Infinite Latent Attribute Models

Zoubin Ghahramani, David A. Knowles, Konstantina Palla, 2015, IEEE Transactions on Pattern Analysis and Machine Intelligence.

Bayesian Hidden Markov models and extensions

Zoubin Ghahramani, 2010, CoNLL 2010.

Discovering latent influence in online social activities via shared cascade poisson processes

Tomoharu Iwata, Zoubin Ghahramani, Amar Shah, 2013, KDD.

Distributed Flexible Nonlinear Tensor Factorization

Zenglin Xu, Zoubin Ghahramani, Kai Zhang, 2016, NIPS.

Probabilistic Models for Incomplete Multi-dimensional Arrays

Wei Chu, Zoubin Ghahramani, Zoubin Ghahramani, 2009, AISTATS.

Statistical Model Criticism using Kernel Two Sample Tests

Zoubin Ghahramani, James Robert Lloyd, Zoubin Ghahramani, 2015, NIPS.

Graph Kernels by Spectral Transforms

Zoubin Ghahramani, Xiaojin Zhu, John Lafferty, 2006, Semi-Supervised Learning.

One-Network Adversarial Fairness

Zoubin Ghahramani, Adrian Weller, Isabel Valera, 2019, AAAI.

Lecture 6: Hierarchical and Nonlinear Models

Zoubin Ghahramani, Zoubin Ghahramani, 2005 .

Antithetic and Monte Carlo kernel estimators for partial rankings

Arthur Gretton, Zoubin Ghahramani, Mark Rowland, 2018, Statistics and Computing.

Learning Nonlinear Dynamical Systems Using an EM Algorithm

Zoubin Ghahramani, Sam T. Roweis, S. Roweis, 1998, NIPS.

Variational Methods

Zoubin Ghahramani, Zoubin Ghahramani, 2014, Computer Vision, A Reference Guide.

Unifying linear dimensionality reduction

Zoubin Ghahramani, John P. Cunningham, J. Cunningham, 2014, 1406.0873.

Computational principles of movement neuroscience

Zoubin Ghahramani, Daniel M. Wolpert, Zoubin Ghahramani, 2000, Nature Neuroscience.

Neural Adaptive Sequential Monte Carlo

Richard E. Turner, Zoubin Ghahramani, Shixiang Gu, 2015, NIPS.

GPflow: A Gaussian Process Library using TensorFlow

Alexis Boukouvalas, James Hensman, Zoubin Ghahramani, 2016, J. Mach. Learn. Res..

A Nonparametric Bayesian Approach to Modeling Overlapping Clusters

Katherine A. Heller, Zoubin Ghahramani, Zoubin Ghahramani, 2007, AISTATS.

The infinite HMM for unsupervised PoS tagging

Zoubin Ghahramani, Andreas Vlachos, Jurgen Van Gael, 2009, EMNLP.

Probabilistic models for data combination in recommender systems

Zoubin Ghahramani, Sinead Williamson, Zoubin Ghahramani, 2008 .

A Nonparametric Bayesian Model for Multiple Clustering with Overlapping Feature Views

Zoubin Ghahramani, Jennifer G. Dy, Donglin Niu, 2012, AISTATS.

Choosing a Variable to Clamp

Zoubin Ghahramani, Frederik Eaton, Zoubin Ghahramani, 2009, International Conference on Artificial Intelligence and Statistics.

Automatic Bayesian Density Analysis pdf

Kristian Kersting, Robert Peharz, Zoubin Ghahramani, 2018, AAAI.

On Sparse Variational Methods and the Kullback-Leibler Divergence between Stochastic Processes

James Hensman, Richard E. Turner, Zoubin Ghahramani, 2015, AISTATS.

Preference learning with Gaussian processes

Wei Chu, Zoubin Ghahramani, Zoubin Ghahramani, 2005, ICML.

The Infinite Factorial Hidden Markov Model

Yee Whye Teh, Zoubin Ghahramani, Jurgen Van Gael, 2008, NIPS.

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

Zoubin Ghahramani, Zoubin Ghahramani, 2007, ICML.

Gaussian Process Behaviour in Wide Deep Neural Networks pdf

Richard E. Turner, Zoubin Ghahramani, Jiri Hron, 2018, ICLR.

Variational Bayesian dropout: pitfalls and fixes pdf

Zoubin Ghahramani, Jiri Hron, Alexander G. de G. Matthews, 2018, ICML.

Learning with Multiple Labels

Rong Jin, Zoubin Ghahramani, Zoubin Ghahramani, 2002, NIPS.

Bayesian segmental models with multiple sequence alignment profiles for protein secondary structure and contact map prediction

Wei Chu, Zoubin Ghahramani, David L. Wild, 2006, IEEE/ACM Transactions on Computational Biology and Bioinformatics.

Randomized Nonlinear Component Analysis pdf

Bernhard Schölkopf, Alexander J. Smola, Zoubin Ghahramani, 2014, ICML.

Bayesian Learning in Undirected Graphical Models

Zoubin Ghahramani, Iain Murray, Hc Kim, 2003 .

A Robust Bayesian Two-Sample Test for Detecting Intervals of Differential Gene Expression in Microarray Time Series

Zoubin Ghahramani, Oliver Stegle, Karsten M. Borgwardt, 2009, RECOMB.

Bayesian Learning in Undirected Graphical Models: Approximate MCMC Algorithms pdf

Zoubin Ghahramani, Iain Murray, Iain Murray, 2004, UAI.

Collaborative Gaussian Processes for Preference Learning

Zoubin Ghahramani, José Miguel Hernández-Lobato, Neil Houlsby, 2012, NIPS.

Bayesian hidden markov models and extensions: Invited talk

Zoubin Ghahramani, Zoubin Ghahramani, 2010 .

Gene function prediction from synthetic lethality networks via ranking on demand

Zoubin Ghahramani, Karsten M. Borgwardt, Christoph Lippert, 2010, Bioinform..

Deep Bayesian Active Learning with Image Data pdf

Zoubin Ghahramani, Yarin Gal, Riashat Islam, 2017, ICML.

Tree-Structured Stick Breaking for Hierarchical Data

Michael I. Jordan, Ryan P. Adams, Zoubin Ghahramani, 2010, NIPS.

Probabilistic Models for Preference Learning

Zoubin Ghahramani, Zoubin Ghahramani, 2011 .

Probabilistic Models for Unsupervised Learning

Zoubin Ghahramani, Sam T. Roweis, S. Roweis, 1999 .

Local and global sparse Gaussian process approximations

Zoubin Ghahramani, Edward Snelson, Zoubin Ghahramani, 2007, AISTATS.

Simultaneous Mapping and Localization with Sparse Extended Information Filters: Theory and Initial Results

Hugh F. Durrant-Whyte, Zoubin Ghahramani, Andrew Y. Ng, 2004, WAFR.

Parameter estimation for linear dynamical systems

Geoffrey E. Hinton, Zoubin Ghahramani, Zoubin Ghahramani, 1996 .

Editors. Advances in Neural Information Processing Systems

Thomas G. Dietterich, Zoubin Ghahramani, Suzanna Becker, 2002 .

A reversible infinite HMM using normalised random measures

Zoubin Ghahramani, David A. Knowles, Konstantina Palla, 2014, ICML.

Copula Processes

Andrew Gordon Wilson, Zoubin Ghahramani, Zoubin Ghahramani, 2010, NIPS.

Turing: Composable inference for probabilistic programming

Kai Xu, Zoubin Ghahramani, Hong Ge, 2018, International Conference on Artificial Intelligence and Statistics.

Random function priors for exchangeable arrays with applications to graphs and relational data

Zoubin Ghahramani, Daniel M. Roy, Peter Orbanz, 2012, NIPS.

Optimal model inference for Bayesian mixture of experts

Zoubin Ghahramani, N. Ueda, 2000, Neural Networks for Signal Processing X. Proceedings of the 2000 IEEE Signal Processing Society Workshop (Cat. No.00TH8501).

Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning pdf

Zoubin Ghahramani, Yarin Gal, Zoubin Ghahramani, 2015, ICML.

One-Shot Learning in Discriminative Neural Networks pdf

Zoubin Ghahramani, James Robert Lloyd, Jordan Burgess, 2017, ArXiv.

Variational Measure Preserving Flows pdf

Zoubin Ghahramani, José Miguel Hernández-Lobato, Yichuan Zhang, 2018, ArXiv.

Improving PPM with Dynamic Parameter Updates

Zoubin Ghahramani, David J. C. MacKay, Christian Steinruecken, 2015, 2015 Data Compression Conference.

Gaussian Processes for time-marked time-series data

Carl E. Rasmussen, Zoubin Ghahramani, John P. Cunningham, 2012, AISTATS.

Dependent Indian Buffet Processes

Zoubin Ghahramani, Peter Orbanz, Sinead Williamson, 2010, AISTATS.

Interpretable Continual Learning

Richard E. Turner, Zoubin Ghahramani, Adrian Weller, 2018 .

Discovering Temporal Patterns of Differential Gene Expression in Microarray Time Series

Zoubin Ghahramani, Andrew Meade, Oliver Stegle, 2009, GCB.

Bayesian Monte Carlo

Carl E. Rasmussen, Zoubin Ghahramani, Zoubin Ghahramani, 2002, NIPS.

Bayesian Inference for Gaussian Mixed Graph Models pdf

Zoubin Ghahramani, Ricardo Bezerra de Andrade e Silva, 2006, UAI.

DynamicPPL: Stan-like Speed for Dynamic Probabilistic Models pdf

Kai Xu, Zoubin Ghahramani, Hong Ge, 2020, ArXiv.

Bayesian Learning of Sum-Product Networks pdf

Franz Pernkopf, Robert Peharz, Zoubin Ghahramani, 2019, NeurIPS.

Partial Membership and Factor Analysis

Katherine A. Heller, Zoubin Ghahramani, Shakir Mohamed, 2014, Handbook of Mixed Membership Models and Their Applications.

IEEE Transactions on Pattern Analysis and Machine Intelligence: Editor's note

Jiri Matas, Zoubin Ghahramani, Ramin Zabih, 2010 .

Scaling the Indian Buffet Process via Submodular Maximization pdf

Zoubin Ghahramani, Colorado Reed, Zoubin Ghahramani, 2013, ICML.

approach to modelling Bayesian non-parametrics and the probabilistic

Zoubin Ghahramani, Zoubin Ghahramani, 2013 .

Active Learning with Statistical Models

David A. Cohn, Michael I. Jordan, Zoubin Ghahramani, 1996, NIPS.

Supervised learning from incomplete data via an EM approach

Michael I. Jordan, Zoubin Ghahramani, Zoubin Ghahramani, 1993, NIPS.

Dirichlet Process Mixture Models for Verb Clustering

Zoubin Ghahramani, Andreas Vlachos, Anna Korhonen, 2008 .

The Mirage of Action-Dependent Baselines in Reinforcement Learning pdf

Sergey Levine, Richard E. Turner, Zoubin Ghahramani, 2018, ICML.

Variational Inference for Nonparametric Multiple Clustering

Zoubin Ghahramani, Jennifer G. Dy, Yue Guan, 2010 .

Variational Learning for Switching State-Space Models

Geoffrey E. Hinton, Zoubin Ghahramani, Zoubin Ghahramani, 2000, Neural Computation.

Gaussian Processes for Ordinal Regression

Wei Chu, Zoubin Ghahramani, Zoubin Ghahramani, 2005, J. Mach. Learn. Res..

Computational motor control

Zoubin Ghahramani, Daniel M. Wolpert, Zoubin Ghahramani, 2004 .

An Infinite Latent Attribute Model for Network Data

Zoubin Ghahramani, David A. Knowles, Konstantina Palla, 2012, ICML.

A note on the evidence and Bayesian Occam's razor

Zoubin Ghahramani, Iain Murray, Iain Murray, 2005 .

Discovering transcriptional modules by Bayesian data integration

Zoubin Ghahramani, Jim E. Griffin, David L. Wild, 2010, Bioinform..

Infinite latent feature models and the Indian buffet process

Thomas L. Griffiths, Zoubin Ghahramani, T. Griffiths, 2005, NIPS.

Computation and psychophysics of sensorimotor integration

Zoubin Ghahramani, Zoubin Ghahramani, 1996 .

Compact approximations to Bayesian predictive distributions

Zoubin Ghahramani, Edward Snelson, Zoubin Ghahramani, 2005, ICML.

Computational neuroscience: Building blocks of movement

Zoubin Ghahramani, Zoubin Ghahramani, 2000, Nature.

Face recognition based on separate lattice HMMs

Yoshihiko Nankaku, Keiichi Tokuda, Tadashi Kitamura, 2006 .

Bayesian Cluster Analysis: Point Estimation and Credible Balls (with Discussion)

Zoubin Ghahramani, Sara Wade, Zoubin Ghahramani, 2015, Bayesian Analysis.

Proceedings of the 24th international conference on Machine learning

Zoubin Ghahramani, Zoubin Ghahramani, 2007, ICML 2007.

Optimization with EM and Expectation-Conjugate-Gradient

Zoubin Ghahramani, Ruslan Salakhutdinov, Sam T. Roweis, 2003, ICML.

Variational Inference for Bayesian Mixtures of Factor Analysers

Zoubin Ghahramani, Matthew J. Beal, Zoubin Ghahramani, 1999, NIPS.

Automating machine learning

Zoubin Ghahramani, 2016 .

The Mondrian Kernel

Yee Whye Teh, Zoubin Ghahramani, Daniel M. Roy, 2016, UAI.

Variational Infinite Hidden Conditional Random Fields

Stefanos Zafeiriou, Maja Pantic, Zoubin Ghahramani, 2015, IEEE Transactions on Pattern Analysis and Machine Intelligence.

An Empirical Study of Stochastic Variational Algorithms for the Beta Bernoulli Process pdf

Zoubin Ghahramani, David A. Knowles, Amar Shah, 2015, ICML 2015.

Learning Dynamic Bayesian Networks

Zoubin Ghahramani, Zoubin Ghahramani, 1997, Summer School on Neural Networks.

Simultaneous Localization and Mapping with Sparse Extended Information Filters

Hugh F. Durrant-Whyte, Zoubin Ghahramani, Andrew Y. Ng, 2004, Int. J. Robotics Res..

The Dynamic Beamformer

Marcel A. J. van Gerven, Tom Heskes, Zoubin Ghahramani, 2011, MLINI.

Functional programming for modular Bayesian inference

Ohad Kammar, Zoubin Ghahramani, Adam Scibior, 2018, Proc. ACM Program. Lang..

Semi-supervised learning : from Gaussian fields to Gaussian processes

Zoubin Ghahramani, Xiaojin Zhu, John Lafferty, 2003 .

Nonparametric Transforms of Graph Kernels for Semi-Supervised Learning

Zoubin Ghahramani, Xiaojin Zhu, John D. Lafferty, 2004, NIPS.

Gender Classification with Bayesian Kernel Methods

Hyun-Chul Kim, Zoubin Ghahramani, Daijin Kim, 2006, The 2006 IEEE International Joint Conference on Neural Network Proceedings.

Reconstructing Transcriptional Networks Using Gene Expression Profiling and Bayesian State-Space Models

Juan Li, Zoubin Ghahramani, Matthew J. Beal, 2007 .

Predictive Entropy Search for Bayesian Optimization with Unknown Constraints

Matthew W. Hoffman, Ryan P. Adams, Zoubin Ghahramani, 2015, ICML.

Latent Gaussian Processes for Distribution Estimation of Multivariate Categorical Data

Zoubin Ghahramani, Yutian Chen, Yarin Gal, 2015, ICML.

Relational Learning with Gaussian Processes

Wei Chu, Zoubin Ghahramani, S. Sathiya Keerthi, 2006, NIPS.

Bayesian Gaussian Process Classification with the EM-EP Algorithm

Hyun-Chul Kim, Zoubin Ghahramani, Zoubin Ghahramani, 2006, IEEE Transactions on Pattern Analysis and Machine Intelligence.

Lecture 6: Graphical Models: Learning

Zoubin Ghahramani, Carl Edward Rasmussen, Zoubin Ghahramani, 2010 .

A Birth-Death Process for Feature Allocation

Zoubin Ghahramani, David A. Knowles, Konstantina Palla, 2017, ICML.

Modeling T-cell activation using gene expression profiling and state-space models

Zoubin Ghahramani, Francesco Falciani, David L. Wild, 2004, Bioinform..

A Comparison of Human and Agent Reinforcement Learning in Partially Observable Domains

Zoubin Ghahramani, Finale Doshi-Velez, Zoubin Ghahramani, 2011, CogSci.

Face Recognition Based on Separable Lattice HMMS

Yoshihiko Nankaku, Keiichi Tokuda, Tadashi Kitamura, 2006, 2006 IEEE International Conference on Acoustics Speech and Signal Processing Proceedings.

A Bayesian approach to reconstructing genetic regulatory networks with hidden factors

Zoubin Ghahramani, Matthew J. Beal, Francesco Falciani, 2005, Bioinform..

Modeling genetic regulatory networks using gene expression profiling and state space models

Zoubin Ghahramani, David L. Wild, John E. Angus, 2005 .

Modeling and Visualizing Uncertainty in Gene Expression Clusters Using Dirichlet Process Mixtures

Zoubin Ghahramani, Carl Edward Rasmussen, David L Wild, 2009, TCBB.

Bayesian Exponential Family PCA

Katherine A. Heller, Zoubin Ghahramani, Shakir Mohamed, 2008, NIPS.

Human Activity Recognition by Combining a Small Number of Classifiers

Zoubin Ghahramani, Antonio Artés-Rodríguez, Alfredo Nazábal, 2016, IEEE Journal of Biomedical and Health Informatics.

General Latent Feature Modeling for Data Exploration Tasks pdf

Zoubin Ghahramani, Isabel Valera, Melanie F. Pradier, 2017, ArXiv.

General Table Completion using a Bayesian Nonparametric Model

Zoubin Ghahramani, Isabel Valera, Zoubin Ghahramani, 2014, NIPS.

Proceedings, Twenty-Fourth International Conference on Machine Learning

Zoubin Ghahramani, Zoubin Ghahramani, 2007 .

Advances in Neural Information Processing Systems 14 [Neural Information Processing Systems: Natural and Synthetic, NIPS 2001, December 3-8, 2001, Vancouver, British Columbia, Canada]

Thomas G. Dietterich, Zoubin Ghahramani, Suzanna Becker, 2001, NIPS.

Warped Mixtures for Nonparametric Cluster Shapes pdf

Tomoharu Iwata, Zoubin Ghahramani, David Duvenaud, 2012, UAI.

A Unifying Review of Linear Gaussian Models

Zoubin Ghahramani, Sam T. Roweis, S. Roweis, 1999, Neural Computation.

Unsupervised learning of sensory-motor synergies

Zoubin Ghahramani, Emanuel Todorov, E. Todorov, 2003 .

Modeling Dyadic Data with Binary Latent Factors

Zoubin Ghahramani, Radford M. Neal, Sam T. Roweis, 2006, NIPS.

Active Learning for Interactive Visualization

Tomoharu Iwata, Zoubin Ghahramani, Neil Houlsby, 2013, AISTATS.

Computational Structure of coordinate transformations: A generalization study

Michael I. Jordan, Zoubin Ghahramani, Daniel M. Wolpert, 1994, NIPS.

Ranking Relations using Analogies in Biological and Information Networks

Edoardo M. Airoldi, Katherine A. Heller, Zoubin Ghahramani, 2009, The annals of applied statistics.

Interpolated Policy Gradient: Merging On-Policy and Off-Policy Gradient Estimation for Deep Reinforcement Learning

Richard E. Turner, Zoubin Ghahramani, Bernhard Scholkopf, 2017, NIPS.

Combining active learning and semi-supervised learning using Gaussian fields and harmonic functions

Zoubin Ghahramani, Xiaojin Zhu, John D. Lafferty, 2003, ICML 2003.

Hierarchical Non-linear Factor Analysis and Topographic Maps

Geoffrey E. Hinton, Zoubin Ghahramani, Zoubin Ghahramani, 1997, NIPS.

A Very Simple Safe-Bayesian Random Forest

Zoubin Ghahramani, Novi Quadrianto, Zoubin Ghahramani, 2015, IEEE Transactions on Pattern Analysis and Machine Intelligence.

Factorial Hidden Markov Models

Carl E. Rasmussen, Zoubin Ghahramani, Matthew J. Beal, 1997 .

Editor's Note

Jiri Matas, Zoubin Ghahramani, Ramin Zabih, 2010, IEEE Trans. Pattern Anal. Mach. Intell..

Extensions of Gaussian processes for ranking: semi-supervised and active learning

Wei Chu, Zoubin Ghahramani, 2005 .

Pitman Yor Diffusion Trees for Bayesian Hierarchical Clustering

Zoubin Ghahramani, David A. Knowles, 2015, IEEE Transactions on Pattern Analysis and Machine Intelligence.

Active learning with mixture models

David A. Cohn, Michael I. Jordan, Zoubin Ghahramani, 1997 .

An Empirical Study of Stochastic Variational Inference Algorithms for the Beta Bernoulli Process

Zoubin Ghahramani, David A. Knowles, Amar Shah, 2015, International Conference on Machine Learning.

Forward dynamic models in human motor control: Psychophysical evidence

Michael I. Jordan, Zoubin Ghahramani, Daniel M. Wolpert, 1994, NIPS.

Slice Sampling for Probabilistic Programming pdf

Zoubin Ghahramani, Razvan Ranca, Zoubin Ghahramani, 2015, ArXiv.

A kernel method for unsupervised structured network inference

Zoubin Ghahramani, Oliver Stegle, Karsten M. Borgwardt, 2009, AISTATS.

The training algorithm based on variational approximation for separable 2D-HMM

Yoshihiko Nankaku, Keiichi Tokuda, Tadashi Kitamura, 2003 .

Bayesian non-parametrics and the probabilistic approach to modelling

Zoubin Ghahramani, Zoubin Ghahramani, 2013, Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences.

Stick-breaking Construction for the Indian Buffet Process

Yee Whye Teh, Dilan Görür, Zoubin Ghahramani, 2007, AISTATS.

Bayesian Convolutional Neural Networks with Bernoulli Approximate Variational Inference pdf

Zoubin Ghahramani, Yarin Gal, Zoubin Ghahramani, 2015, ArXiv.

Analogical Reasoning with Relational Bayesian Sets

Katherine A. Heller, Zoubin Ghahramani, Ricardo Bezerra de Andrade e Silva, 2007, AISTATS.

Message Passing Algorithms for the Dirichlet Diffusion Tree

Zoubin Ghahramani, David A. Knowles, Jurgen Van Gael, 2011, ICML.

A Tutorial on Gaussian Processes (or why I don't use SVMs)

Zoubin Ghahramani, Zoubin Ghahramani, 2011 .

A new approach to data driven clustering

Zoubin Ghahramani, Arik Azran, Zoubin Ghahramani, 2006, ICML.

Modelling Input Varying Correlations between Multiple Responses

Andrew Gordon Wilson, Zoubin Ghahramani, 2012, ECML/PKDD.

Kernel conditional graphical models

Zoubin Ghahramani, Massimiliano Pontil, F Perez Cruz, 2007 .

Learning the Structure of Deep Sparse Graphical Models

Ryan P. Adams, Zoubin Ghahramani, Hanna M. Wallach, 2009, AISTATS.

Zoubin Ghahramani, Jim E. Griffin, Paul D. W. Kirk, 2012, Bioinform..

Handling Incomplete Heterogeneous Data using VAEs pdf

Pablo M. Olmos, Zoubin Ghahramani, Isabel Valera, 2018, Pattern Recognit..

Conditional Graphical Models

Zoubin Ghahramani, Massimiliano Pontil, Fernando Perez-Cruz, 2007 .

Copula-based Kernel Dependency Measures pdf

Barnabás Póczos, Zoubin Ghahramani, Jeff G. Schneider, 2012, ICML.

Factorial Learning and the EM Algorithm

Zoubin Ghahramani, Zoubin Ghahramani, 1994, NIPS.

Statistical models for partial membership

Katherine A. Heller, Zoubin Ghahramani, Sinead Williamson, 2008, ICML '08.

Degrees of freedom and hand synergies in manipulation tasks

Zoubin Ghahramani, Emanuel Todorov, E. Todorov, 2000 .

A Non-parametric Conditional Factor Regression Model for Multi-Dimensional Input and Response

Zoubin Ghahramani, Richard Yi Da Xu, Massimo Piccardi, 2014, AISTATS.

Message passing algorithms for dirichlet diffusion trees

Zoubin Ghahramani, David A. Knowles, Jurgen Van Gael, 2011, ICML 2011.

Automatic Construction and Natural-Language Description of Nonparametric Regression Models

Joshua B. Tenenbaum, Zoubin Ghahramani, Roger B. Grosse, 2014, AAAI.

A graphical model for protein secondary structure prediction

Wei Chu, Zoubin Ghahramani, David L. Wild, 2004, ICML.

Bayesian Methods for Artificial Intelligence and Machine Learning

Zoubin Ghahramani, 2008, ECAI.

Warped Gaussian Processes

Carl E. Rasmussen, Zoubin Ghahramani, Edward Snelson, 2003, NIPS.

Bayesian inference on random simple graphs with power law degree distributions

Zoubin Ghahramani, Seungjin Choi, Juho Lee, 2017, ICML.

Generalised Wishart Processes

Andrew Gordon Wilson, Zoubin Ghahramani, Zoubin Ghahramani, 2010, UAI.

The delve manual

Geoffrey E. Hinton, Robert Tibshirani, Zoubin Ghahramani, 1996 .

Modeling and Visualizing Uncertainty in Gene Expression Clusters Using Dirichlet Process Mixtures

Carl E. Rasmussen, Zoubin Ghahramani, David L. Wild, 2009, IEEE/ACM Transactions on Computational Biology and Bioinformatics.

The Block Diagonal Infinite Hidden Markov Model

Tai Sing Lee, Zoubin Ghahramani, Geoffrey J. Gordon, 2009, AISTATS.

Gaussian Process Volatility Model

Zoubin Ghahramani, José Miguel Hernández-Lobato, Yue Wu, 2014, NIPS.

Modular decomposition in visuomotor learning

Zoubin Ghahramani, Daniel M. Wolpert, Zoubin Ghahramani, 1997, Nature.

Learning to Parse Images

Yee Whye Teh, Geoffrey E. Hinton, Zoubin Ghahramani, 1999, NIPS.

The Random Forest Kernel and other kernels for big data from random partitions pdf

Zoubin Ghahramani, Alex Davies, Zoubin Ghahramani, 2014, ArXiv.

A Simple Bayesian Framework for Content-Based Image Retrieval

Katherine A. Heller, Zoubin Ghahramani, Zoubin Ghahramani, 2006, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06).

Introduction of New Associate Editors

David J. Fleet, David J. Kriegman, Zoubin Ghahramani, 2008, IEEE Trans. Pattern Anal. Mach. Intell..

Bayesian Support Vector Machines for Feature Ranking and Selection

Wei Chu, Zoubin Ghahramani, S. Sathiya Keerthi, 2006, Feature Extraction.

U-Likelihood and U-Updating Algorithms: Statistical Inference in Latent Variable Models

Zoubin Ghahramani, Seungjin Choi, Sung Yang Bang, 2005, ECML.

Occam's Razor

Carl E. Rasmussen, Zoubin Ghahramani, Zoubin Ghahramani, 2000, NIPS.

Introduction of New Associate Editors

Jiri Matas, Zoubin Ghahramani, Ramin Zabih, 2008, IEEE Trans. Pattern Anal. Mach. Intell..

A Bayesian approach to information retrieval from sets of items

Katherine A. Heller, Zoubin Ghahramani, Zoubin Ghahramani, 2006 .

Second-Order Latent-Space Variational Bayes for Approximate Bayesian Inference

Zoubin Ghahramani, Sung Yang Bang, JaeMo Sung, 2008, IEEE Signal Processing Letters.

Weakly supervised collective feature learning from curated media

Zoubin Ghahramani, Akisato Kimura, Yusuke Mukuta, 2018, AAAI.

Flexible latent variable models for multi-task learning

Yiming Yang, Zoubin Ghahramani, Jian Zhang, 2008, Machine Learning.

How machines learned to think statistically

Zoubin Ghahramani, Brian Tarran, 2015 .

Avoiding pathologies in very deep networks

Ryan P. Adams, Zoubin Ghahramani, David Duvenaud, 2014, AISTATS.

Discovering Interpretable Representations for Both Deep Generative and Discriminative Models

Zoubin Ghahramani, Adrian Weller, Tameem Adel, 2018, ICML.

Nested sampling for Potts models

Zoubin Ghahramani, Iain Murray, John Skilling, 2005, NIPS.

Modelling biological responses using gene expression profiling and linear dynamical systems

Zoubin Ghahramani, Francesco Falciani, David L. Wild, 2001 .

Editor's Note

Jiri Matas, Zoubin Ghahramani, Sing Bing Kang, 2011, IEEE Transactions on Pattern Analysis and Machine Intelligence.

A Probabilistic Model for Online Document Clustering with Application to Novelty Detection

Yiming Yang, Zoubin Ghahramani, Jian Zhang, 2004, NIPS.

Approximate inference for the loss-calibrated Bayesian

Zoubin Ghahramani, Ferenc Huszar, Simon Lacoste-Julien, 2011, AISTATS.

Subsampling-Based Approximate Monte Carlo for Discrete Distributions pdf

Zoubin Ghahramani, Yutian Chen, Zoubin Ghahramani, 2015, ArXiv.

6 LEARNING NONLINEAR DYNAMICAL SYSTEMS USING THE EXPECTATION – MAXIMIZATION ALGORITHM

Zoubin Ghahramani, S. Roweis, Zoubin Ghahramani, 2001 .

Representative Subgraph Sampling using Markov Chain Monte Carlo Methods

Hans-Peter Kriegel, Zoubin Ghahramani, Karsten Borgwardt, 2008 .

Pattern classification using a mixture of factor analyzers

Geoffrey E. Hinton, Naonori Ueda, Zoubin Ghahramani, 1999, Neural Networks for Signal Processing IX: Proceedings of the 1999 IEEE Signal Processing Society Workshop (Cat. No.98TH8468).

Active Learning for Constrained Dirichlet Process Mixture Models

Ted Briscoe, Zoubin Ghahramani, Andreas Vlachos, 2010 .

Identifying cancer subtypes in glioblastoma by combining genomic, transcriptomic and epigenomic data

Zoubin Ghahramani, Jim E. Griffin, David L. Wild, 2013 .

Learning about protein hydrogen bonding by minimizing contrastive divergence

Zoubin Ghahramani, David L Wild, Zoubin Ghahramani, 2006, Proteins.

The Random Forest Kernel and creating other kernels for big data from random partitions

Zoubin Ghahramani, Alex Davies, 2014 .

Fast online anomaly detection using scan statistics

Zoubin Ghahramani, Steven Bottone, Ryan Turner, 2010, 2010 IEEE International Workshop on Machine Learning for Signal Processing.

Ergodic Measure Preserving Flows

Zoubin Ghahramani, José Miguel Hernández-Lobato, Yichuan Zhang, 2018 .