Zoubin Ghahramani

329 papers A* 56A 44B 8C 3Misc 3Journal 132Unranked 74

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Efficiently Reconstructing Dynamic Scenes One D4RT at a Time. CoRR Chuhan Zhang, Guillaume Le Moing, Skanda Koppula, Ignacio Rocco, Liliane Momeni, Junyu Xie, Shuyang Sun, Rahul Sukthankar, Joëlle K. Barral, Raia Hadsell, Zoubin Ghahramani, Andrew Zisserman, Junlin Zhang, Mehdi S. M. Sajjadi
2024	J	`jnl`	Pre-trained Gaussian Processes for Bayesian Optimization. J. Mach. Learn. Res. Zi Wang, George E. Dahl, Kevin Swersky, Chansoo Lee, Zachary Nado, Justin Gilmer, Jasper Snoek, Zoubin Ghahramani
2024	J	`jnl`	RecurrentGemma: Moving Past Transformers for Efficient Open Language Models. CoRR Aleksandar Botev, Soham De, Samuel L. Smith, Anushan Fernando, George-Cristian Muraru, Ruba Haroun, Leonard Berrada, Razvan Pascanu, Pier Giuseppe Sessa, Robert Dadashi, Léonard Hussenot, Johan Ferret, Sertan Girgin, Olivier Bachem, Alek Andreev, Kathleen Kenealy, Thomas Mesnard, Cassidy Hardin, Surya Bhupatiraju, Shreya Pathak, Laurent Sifre, Morgane Rivière, Mihir Sanjay Kale, Juliette Love, Pouya Tafti, Armand Joulin, Noah Fiedel, Evan Senter, Yutian Chen, Srivatsan Srinivasan, Guillaume Desjardins, David Budden, Arnaud Doucet, Sharad Vikram, Adam Paszke, Trevor Gale, Sebastian Borgeaud, Charlie Chen, Andy Brock, Antonia Paterson, Jenny Brennan, Meg Risdal, Raj Gundluru, Nesh Devanathan, Paul Mooney, Nilay Chauhan, Phil Culliton, Luiz Gustavo Martins, Elisa Bandy, David Huntsperger, Glenn Cameron, Arthur Zucker, Tris Warkentin, Ludovic Peran, Minh Giang, Zoubin Ghahramani, Clément Farabet, Koray Kavukcuoglu, Demis Hassabis, Raia Hadsell, Yee Whye Teh, Nando de Frietas
2024	J	`jnl`	Resource-Efficient Neural Networks for Embedded Systems. J. Mach. Learn. Res. Wolfgang Roth, Günther Schindler, Bernhard Klein, Robert Peharz, Sebastian Tschiatschek, Holger Fröning, Franz Pernkopf, Zoubin Ghahramani
2024	J	`jnl`	Rethinking the Role of Bayesianism in the Age of Modern AI (Dagstuhl Seminar 24461). Dagstuhl Reports Vincent Fortuin, Mohammad Emtiyaz Khan, Mark van der Wilk, Zoubin Ghahramani, Katharine Fisher
2024	J	`jnl`	Towards Responsible Development of Generative AI for Education: An Evaluation-Driven Approach. CoRR Irina Jurenka, Markus Kunesch, Kevin R. McKee, Daniel Gillick, Shaojian Zhu, Sara Wiltberger, Shubham Milind Phal, Katherine L. Hermann, Daniel Kasenberg, Avishkar Bhoopchand, Ankit Anand, Miruna Pîslar, Stephanie Chan, Lisa Wang, Jennifer She, Parsa Mahmoudieh, Aliya Rysbek, Wei-Jen Ko, Andrea Huber, Brett Wiltshire, Gal Elidan, Roni Rabin, Jasmin Rubinovitz, Amit Pitaru, Mac McAllister, Julia Wilkowski, David Choi, Roee Engelberg, Lidan Hackmon, Adva Levin, Rachel Griffin, Michael Sears, Filip Bar, Mia Mesar, Mana Jabbour, Arslan Chaudhry, James Cohan, Sridhar Thiagarajan, Nir Levine, Ben Brown, Dilan Görür, Svetlana Grant, Rachel Hashimshoni, Laura Weidinger, Jieru Hu, Dawn Chen, Kuba Dolecki, Canfer Akbulut, Maxwell L. Bileschi, Laura Culp, Wen-Xin Dong, Nahema Marchal, Kelsie Van Deman, Hema Bajaj Misra, Michael Duah, Moran Ambar, Avi Caciularu, Sandra Lefdal, Christopher Summerfield, James An, Pierre-Alexandre Kamienny, Abhinit Mohdi, Theofilos Strinopoulos, Annie Hale, Wayne Anderson, Luis C. Cobo, Niv Efron, Muktha Ananda, Shakir Mohamed, Maureen Heymans, Zoubin Ghahramani, Yossi Matias, Ben Gomes, Lila Ibrahim
2023	A*	`conf`	Neural Diffusion Processes. ICML Vincent Dutordoir, Alan Saul, Zoubin Ghahramani, Fergus Simpson
2022	J	`jnl`	Neural Diffusion Processes. CoRR Vincent Dutordoir, Alan Saul, Zoubin Ghahramani, Fergus Simpson
2022	J	`jnl`	Plex: Towards Reliability using Pretrained Large Model Extensions. CoRR Dustin Tran, Jeremiah Z. Liu, Michael W. Dusenberry, Du Phan, Mark Collier, Jie Ren, Kehang Han, Zi Wang, Zelda Mariet, Huiyi Hu, Neil Band, Tim G. J. Rudner, Karan Singhal, Zachary Nado, Joost van Amersfoort, Andreas Kirsch, Rodolphe Jenatton, Nithum Thain, Honglin Yuan, Kelly Buchanan, Kevin Murphy, D. Sculley, Yarin Gal, Zoubin Ghahramani, Jasper Snoek, Balaji Lakshminarayanan
2022	J	`jnl`	Pre-training helps Bayesian optimization too. CoRR Zi Wang, George E. Dahl, Kevin Swersky, Chansoo Lee, Zelda Mariet, Zachary Nado, Justin Gilmer, Jasper Snoek, Zoubin Ghahramani
2021	J	`jnl`	Automatic prior selection for meta Bayesian optimization with a case study on tuning deep neural network optimizers. CoRR Zi Wang, George E. Dahl, Kevin Swersky, Chansoo Lee, Zelda Mariet, Zachary Nado, Justin Gilmer, Jasper Snoek, Zoubin Ghahramani
2021	A*	`conf`	Deep Neural Networks as Point Estimates for Deep Gaussian Processes. NeurIPS Vincent Dutordoir, James Hensman, Mark van der Wilk, Carl Henrik Ek, Zoubin Ghahramani, Nicolas Durrande
2021	J	`jnl`	Deep Neural Networks as Point Estimates for Deep Gaussian Processes. CoRR Vincent Dutordoir, James Hensman, Mark van der Wilk, Carl Henrik Ek, Zoubin Ghahramani, Nicolas Durrande
2020	J	`jnl`	DynamicPPL: Stan-like Speed for Dynamic Probabilistic Models. CoRR Mohamed Tarek, Kai Xu, Martin Trapp, Hong Ge, Zoubin Ghahramani
2020	A*	`conf`	Einsum Networks: Fast and Scalable Learning of Tractable Probabilistic Circuits. ICML Robert Peharz, Steven Lang, Antonio Vergari, Karl Stelzner, Alejandro Molina, Martin Trapp, Guy Van den Broeck, Kristian Kersting, Zoubin Ghahramani
2020	J	`jnl`	Einsum Networks: Fast and Scalable Learning of Tractable Probabilistic Circuits. CoRR Robert Peharz, Steven Lang, Antonio Vergari, Karl Stelzner, Alejandro Molina, Martin Trapp, Guy Van den Broeck, Kristian Kersting, Zoubin Ghahramani
2020	J	`jnl`	General Latent Feature Models for Heterogeneous Datasets. J. Mach. Learn. Res. Isabel Valera, Melanie F. Pradier, Maria Lomeli, Zoubin Ghahramani
2020	J	`jnl`	Handling incomplete heterogeneous data using VAEs. Pattern Recognit. Alfredo Nazábal, Pablo M. Olmos, Zoubin Ghahramani, Isabel Valera
2020	J	`jnl`	Learning Continuous Treatment Policy and Bipartite Embeddings for Matching with Heterogeneous Causal Effects. CoRR Will Y. Zou, Smitha Shyam, Michael Mui, Mingshi Wang, Jan O. Pedersen, Zoubin Ghahramani
2020	J	`jnl`	Resource-Efficient Neural Networks for Embedded Systems. CoRR Wolfgang Roth, Günther Schindler, Matthias Zöhrer, Lukas Pfeifenberger, Robert Peharz, Sebastian Tschiatschek, Holger Fröning, Franz Pernkopf, Zoubin Ghahramani
2019	—	`conf`	AdvancedHMC.jl: A robust, modular and e cient implementation of advanced HMC algorithms. AABI Kai Xu, Hong Ge, Will Tebbutt, Mohamed Tarek, Martin Trapp, Zoubin Ghahramani
2019	J	`jnl`	Antithetic and Monte Carlo kernel estimators for partial rankings. Stat. Comput. Maria Lomeli, Mark Rowland, Arthur Gretton, Zoubin Ghahramani
2019	A*	`conf`	Automatic Bayesian Density Analysis. AAAI Antonio Vergari, Alejandro Molina, Robert Peharz, Zoubin Ghahramani, Kristian Kersting, Isabel Valera
2019	A*	`conf`	Bayesian Learning of Sum-Product Networks. NeurIPS Martin Trapp, Robert Peharz, Hong Ge, Franz Pernkopf, Zoubin Ghahramani
2019	J	`jnl`	Bayesian Learning of Sum-Product Networks. CoRR Martin Trapp, Robert Peharz, Hong Ge, Franz Pernkopf, Zoubin Ghahramani
2019	A*	`conf`	One-Network Adversarial Fairness. AAAI Tameem Adel, Isabel Valera, Zoubin Ghahramani, Adrian Weller
2019	A	`conf`	Random Sum-Product Networks: A Simple and Effective Approach to Probabilistic Deep Learning. UAI Robert Peharz, Antonio Vergari, Karl Stelzner, Alejandro Molina, Martin Trapp, Xiaoting Shao, Kristian Kersting, Zoubin Ghahramani
2019	—	`ch.`	The Automatic Statistician. Automated Machine Learning Christian Steinruecken, Emma Smith, David Janz, James Robert Lloyd, Zoubin Ghahramani
2018	J	`jnl`	Antithetic and Monte Carlo kernel estimators for partial rankings. CoRR Maria Lomeli, Mark Rowland, Arthur Gretton, Zoubin Ghahramani
2018	J	`jnl`	Automatic Bayesian Density Analysis. CoRR Antonio Vergari, Alejandro Molina, Robert Peharz, Zoubin Ghahramani, Kristian Kersting, Isabel Valera
2018	J	`jnl`	Branch-recombinant Gaussian processes for analysis of perturbations in biological time series. Bioinform. Christopher A. Penfold, Anastasiya Sybirna, John E. Reid, Yun Huang, Lorenz Wernisch, Zoubin Ghahramani, Murray Grant, M. Azim Surani
2018	J	`jnl`	Denotational validation of higher-order Bayesian inference. Proc. ACM Program. Lang. Adam Scibior, Ohad Kammar, Matthijs Vákár, Sam Staton, Hongseok Yang, Yufei Cai, Klaus Ostermann, Sean K. Moss, Chris Heunen, Zoubin Ghahramani
2018	A*	`conf`	Discovering Interpretable Representations for Both Deep Generative and Discriminative Models. ICML Tameem Adel, Zoubin Ghahramani, Adrian Weller
2018	J	`jnl`	Efficient and Robust Machine Learning for Real-World Systems. CoRR Franz Pernkopf, Wolfgang Roth, Matthias Zöhrer, Lukas Pfeifenberger, Günther Schindler, Holger Fröning, Sebastian Tschiatschek, Robert Peharz, Matthew Mattina, Zoubin Ghahramani
2018	A	`conf`	Few-shot learning of neural networks from scratch by pseudo example optimization. BMVC Akisato Kimura, Zoubin Ghahramani, Koh Takeuchi, Tomoharu Iwata, Naonori Ueda
2018	J	`jnl`	Functional programming for modular Bayesian inference. Proc. ACM Program. Lang. Adam Scibior, Ohad Kammar, Zoubin Ghahramani
2018	—	`conf`	Gaussian Process Behaviour in Wide Deep Neural Networks. ICLR (Poster) Alexander G. de G. Matthews, Jiri Hron, Mark Rowland, Richard E. Turner, Zoubin Ghahramani
2018	J	`jnl`	Gaussian Process Behaviour in Wide Deep Neural Networks. CoRR Alexander G. de G. Matthews, Mark Rowland, Jiri Hron, Richard E. Turner, Zoubin Ghahramani
2018	J	`jnl`	Handling Incomplete Heterogeneous Data using VAEs. CoRR Alfredo Nazábal, Pablo M. Olmos, Zoubin Ghahramani, Isabel Valera
2018	J	`jnl`	Imitation networks: Few-shot learning of neural networks from scratch. CoRR Akisato Kimura, Zoubin Ghahramani, Koh Takeuchi, Tomoharu Iwata, Naonori Ueda
2018	A*	`conf`	MetaGAN: An Adversarial Approach to Few-Shot Learning. NeurIPS Ruixiang Zhang, Tong Che, Zoubin Ghahramani, Yoshua Bengio, Yangqiu Song
2018	J	`jnl`	Probabilistic Deep Learning using Random Sum-Product Networks. CoRR Robert Peharz, Antonio Vergari, Karl Stelzner, Alejandro Molina, Martin Trapp, Kristian Kersting, Zoubin Ghahramani
2018	J	`jnl`	Probabilistic Meta-Representations Of Neural Networks. CoRR Theofanis Karaletsos, Peter Dayan, Zoubin Ghahramani
2018	—	`conf`	The Mirage of Action-Dependent Baselines in Reinforcement Learning. ICLR (Workshop) George Tucker, Surya Bhupatiraju, Shixiang Gu, Richard E. Turner, Zoubin Ghahramani, Sergey Levine
2018	A*	`conf`	The Mirage of Action-Dependent Baselines in Reinforcement Learning. ICML George Tucker, Surya Bhupatiraju, Shixiang Gu, Richard E. Turner, Zoubin Ghahramani, Sergey Levine
2018	J	`jnl`	The Mirage of Action-Dependent Baselines in Reinforcement Learning. CoRR George Tucker, Surya Bhupatiraju, Shixiang Gu, Richard E. Turner, Zoubin Ghahramani, Sergey Levine
2018	A	`conf`	Turing: Composable inference for probabilistic programming. AISTATS Hong Ge, Kai Xu, Zoubin Ghahramani
2018	A*	`conf`	Variational Bayesian dropout: pitfalls and fixes. ICML Jiri Hron, Alexander G. de G. Matthews, Zoubin Ghahramani
2018	J	`jnl`	Variational Bayesian dropout: pitfalls and fixes. CoRR Jiri Hron, Alexander G. de G. Matthews, Zoubin Ghahramani
2018	J	`jnl`	Variational Measure Preserving Flows. CoRR Yichuan Zhang, José Miguel Hernández-Lobato, Zoubin Ghahramani
2018	A*	`conf`	Weakly Supervised Collective Feature Learning From Curated Media. AAAI Yusuke Mukuta, Akisato Kimura, David B. Adrian, Zoubin Ghahramani
2018	J	`jnl`	Weakly supervised collective feature learning from curated media. CoRR Yusuke Mukuta, Akisato Kimura, David B. Adrian, Zoubin Ghahramani
2017	A*	`conf`	A Birth-Death Process for Feature Allocation. ICML Konstantina Palla, David A. Knowles, Zoubin Ghahramani
2017	A*	`conf`	Automatic Discovery of the Statistical Types of Variables in a Dataset. ICML Isabel Valera, Zoubin Ghahramani
2017	A*	`conf`	Bayesian inference on random simple graphs with power law degree distributions. ICML Juho Lee, Creighton Heaukulani, Zoubin Ghahramani, Lancelot F. James, Seungjin Choi
2017	A*	`conf`	Deep Bayesian Active Learning with Image Data. ICML Yarin Gal, Riashat Islam, Zoubin Ghahramani
2017	J	`jnl`	Deep Bayesian Active Learning with Image Data. CoRR Yarin Gal, Riashat Islam, Zoubin Ghahramani
2017	J	`jnl`	Denotational validation of higher-order Bayesian inference. CoRR Adam Scibior, Ohad Kammar, Matthijs Vákár, Sam Staton, Hongseok Yang, Yufei Cai, Klaus Ostermann, Sean K. Moss, Chris Heunen, Zoubin Ghahramani
2017	J	`jnl`	GPflow: A Gaussian Process Library using TensorFlow. J. Mach. Learn. Res. Alexander G. de G. Matthews, Mark van der Wilk, Tom Nickson, Keisuke Fujii, Alexis Boukouvalas, Pablo León-Villagrá, Zoubin Ghahramani, James Hensman
2017	J	`jnl`	General Latent Feature Modeling for Data Exploration Tasks. CoRR Isabel Valera, Melanie F. Pradier, Zoubin Ghahramani
2017	—	`conf`	Interpolated Policy Gradient: Merging On-Policy and Off-Policy Gradient Estimation for Deep Reinforcement Learning. NIPS Shixiang Gu, Tim Lillicrap, Richard E. Turner, Zoubin Ghahramani, Bernhard Schölkopf, Sergey Levine
2017	J	`jnl`	Interpolated Policy Gradient: Merging On-Policy and Off-Policy Gradient Estimation for Deep Reinforcement Learning. CoRR Shixiang Gu, Timothy P. Lillicrap, Zoubin Ghahramani, Richard E. Turner, Bernhard Schölkopf, Sergey Levine
2017	A*	`conf`	Lost Relatives of the Gumbel Trick. ICML Matej Balog, Nilesh Tripuraneni, Zoubin Ghahramani, Adrian Weller
2017	J	`jnl`	Lost Relatives of the Gumbel Trick. CoRR Matej Balog, Nilesh Tripuraneni, Zoubin Ghahramani, Adrian Weller
2017	A*	`conf`	Magnetic Hamiltonian Monte Carlo. ICML Nilesh Tripuraneni, Mark Rowland, Zoubin Ghahramani, Richard E. Turner
2017	J	`jnl`	One-Shot Learning in Discriminative Neural Networks. CoRR Jordan Burgess, James Robert Lloyd, Zoubin Ghahramani
2017	—	`conf`	Q-Prop: Sample-Efficient Policy Gradient with An Off-Policy Critic. ICLR Shixiang Gu, Timothy P. Lillicrap, Zoubin Ghahramani, Richard E. Turner, Sergey Levine
2016	J	`jnl`	A General Framework for Constrained Bayesian Optimization using Information-based Search. J. Mach. Learn. Res. José Miguel Hernández-Lobato, Michael A. Gelbart, Ryan P. Adams, Matthew W. Hoffman, Zoubin Ghahramani
2016	—	`conf`	A Theoretically Grounded Application of Dropout in Recurrent Neural Networks. NIPS Yarin Gal, Zoubin Ghahramani
2016	J	`jnl`	A study of the effect of JPG compression on adversarial images. CoRR Gintare Karolina Dziugaite, Zoubin Ghahramani, Daniel M. Roy
2016	A	`conf`	Bayesian Generalised Ensemble Markov Chain Monte Carlo. AISTATS Jes Frellsen, Ole Winther, Zoubin Ghahramani, Jesper Ferkinghoff-Borg
2016	—	`conf`	Distributed Flexible Nonlinear Tensor Factorization. NIPS Shandian Zhe, Kai Zhang, Pengyuan Wang, Kuang-Chih Lee, Zenglin Xu, Yuan Qi, Zoubin Ghahramani
2016	A*	`conf`	Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning. ICML Yarin Gal, Zoubin Ghahramani
2016	J	`jnl`	Human Activity Recognition by Combining a Small Number of Classifiers. IEEE J. Biomed. Health Informatics Alfredo Nazábal, Pablo Garcia-Moreno, Antonio Artés-Rodríguez, Zoubin Ghahramani
2016	A	`conf`	Markov Beta Processes for Time Evolving Dictionary Learning. UAI Amar Shah, Zoubin Ghahramani
2016	A	`conf`	On Sparse Variational Methods and the Kullback-Leibler Divergence between Stochastic Processes. AISTATS Alexander G. de G. Matthews, James Hensman, Richard E. Turner, Zoubin Ghahramani
2016	A*	`conf`	Pareto Frontier Learning with Expensive Correlated Objectives. ICML Amar Shah, Zoubin Ghahramani
2016	J	`jnl`	Q-Prop: Sample-Efficient Policy Gradient with An Off-Policy Critic. CoRR Shixiang Gu, Timothy P. Lillicrap, Zoubin Ghahramani, Richard E. Turner, Sergey Levine
2016	A*	`conf`	Scalable Discrete Sampling as a Multi-Armed Bandit Problem. ICML Yutian Chen, Zoubin Ghahramani
2016	A	`conf`	The Mondrian Kernel. UAI Matej Balog, Balaji Lakshminarayanan, Zoubin Ghahramani, Daniel M. Roy, Yee Whye Teh
2016	J	`jnl`	Unsupervised Many-to-Many Object Matching for Relational Data. IEEE Trans. Pattern Anal. Mach. Intell. Tomoharu Iwata, James Robert Lloyd, Zoubin Ghahramani
2015	A*	`conf`	A Probabilistic Model for Dirty Multi-task Feature Selection. ICML Daniel Hernández-Lobato, José Miguel Hernández-Lobato, Zoubin Ghahramani
2015	J	`jnl`	A Very Simple Safe-Bayesian Random Forest. IEEE Trans. Pattern Anal. Mach. Intell. Novi Quadrianto, Zoubin Ghahramani
2015	J	`jnl`	An Empirical Study of Stochastic Variational Algorithms for the Beta Bernoulli Process. CoRR Amar Shah, David A. Knowles, Zoubin Ghahramani
2015	A*	`conf`	An Empirical Study of Stochastic Variational Inference Algorithms for the Beta Bernoulli Process. ICML Amar Shah, David A. Knowles, Zoubin Ghahramani
2015	J	`jnl`	Bayesian Convolutional Neural Networks with Bernoulli Approximate Variational Inference. CoRR Yarin Gal, Zoubin Ghahramani
2015	A*	`conf`	Distributed Inference for Dirichlet Process Mixture Models. ICML Hong Ge, Yutian Chen, Moquan Wan, Zoubin Ghahramani
2015	J	`jnl`	Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning. CoRR Yarin Gal, Zoubin Ghahramani
2015	J	`jnl`	GPstruct: Bayesian Structured Prediction Using Gaussian Processes. IEEE Trans. Pattern Anal. Mach. Intell. Sébastien Bratières, Novi Quadrianto, Zoubin Ghahramani
2015	B	`conf`	Improving PPM with Dynamic Parameter Updates. DCC Christian Steinruecken, Zoubin Ghahramani, David J. C. MacKay
2015	A*	`conf`	Latent Gaussian Processes for Distribution Estimation of Multivariate Categorical Data. ICML Yarin Gal, Yutian Chen, Zoubin Ghahramani
2015	J	`jnl`	Linear dimensionality reduction: survey, insights, and generalizations. J. Mach. Learn. Res. John P. Cunningham, Zoubin Ghahramani
2015	—	`conf`	MCMC for Variationally Sparse Gaussian Processes. NIPS James Hensman, Alexander G. de G. Matthews, Maurizio Filippone, Zoubin Ghahramani
2015	—	`conf`	Neural Adaptive Sequential Monte Carlo. NIPS Shixiang Gu, Zoubin Ghahramani, Richard E. Turner
2015	J	`jnl`	Neural Adaptive Sequential Monte Carlo. CoRR Shixiang Gu, Zoubin Ghahramani, Richard E. Turner
2015	—	`conf`	Parallel Predictive Entropy Search for Batch Global Optimization of Expensive Objective Functions. NIPS Amar Shah, Zoubin Ghahramani
2015	J	`jnl`	Parallel Predictive Entropy Search for Batch Global Optimization of Expensive Objective Functions. CoRR Amar Shah, Zoubin Ghahramani
2015	—	`conf`	Particle Gibbs for Infinite Hidden Markov Models. NIPS Nilesh Tripuraneni, Shixiang Gu, Hong Ge, Zoubin Ghahramani
2015	J	`jnl`	Pitman Yor Diffusion Trees for Bayesian Hierarchical Clustering. IEEE Trans. Pattern Anal. Mach. Intell. David A. Knowles, Zoubin Ghahramani
2015	C	`conf`	Practical probabilistic programming with monads. Haskell Adam Scibior, Zoubin Ghahramani, Andrew D. Gordon
2015	A*	`conf`	Predictive Entropy Search for Bayesian Optimization with Unknown Constraints. ICML José Miguel Hernández-Lobato, Michael A. Gelbart, Matthew W. Hoffman, Ryan P. Adams, Zoubin Ghahramani
2015	J	`jnl`	Probabilistic machine learning and artificial intelligence. Nat. Zoubin Ghahramani
2015	J	`jnl`	Relational Learning and Network Modelling Using Infinite Latent Attribute Models. IEEE Trans. Pattern Anal. Mach. Intell. Konstantina Palla, David A. Knowles, Zoubin Ghahramani
2015	J	`jnl`	Sandwiching the marginal likelihood using bidirectional Monte Carlo. CoRR Roger B. Grosse, Zoubin Ghahramani, Ryan P. Adams
2015	A	`conf`	Scalable Variational Gaussian Process Classification. AISTATS James Hensman, Alexander G. de G. Matthews, Zoubin Ghahramani
2015	J	`jnl`	Slice Sampling for Probabilistic Programming. CoRR Razvan Ranca, Zoubin Ghahramani
2015	—	`conf`	Statistical Model Criticism using Kernel Two Sample Tests. NIPS James Robert Lloyd, Zoubin Ghahramani
2015	J	`jnl`	Subsampling-Based Approximate Monte Carlo for Discrete Distributions. CoRR Yutian Chen, Zoubin Ghahramani
2015	A	`conf`	Training generative neural networks via Maximum Mean Discrepancy optimization. UAI Gintare Karolina Dziugaite, Daniel M. Roy, Zoubin Ghahramani
2015	J	`jnl`	Training generative neural networks via Maximum Mean Discrepancy optimization. CoRR Gintare Karolina Dziugaite, Daniel M. Roy, Zoubin Ghahramani
2015	J	`jnl`	Variational Infinite Hidden Conditional Random Fields. IEEE Trans. Pattern Anal. Mach. Intell. Konstantinos Bousmalis, Stefanos Zafeiriou, Louis-Philippe Morency, Maja Pantic, Zoubin Ghahramani
2014	A	`conf`	A Non-parametric Conditional Factor Regression Model for Multi-Dimensional Input and Response. AISTATS Ava Bargi, Richard Yi Da Xu, Zoubin Ghahramani, Massimo Piccardi
2014	A*	`conf`	A reversible infinite HMM using normalised random measures. ICML David A. Knowles, Zoubin Ghahramani, Konstantina Palla
2014	—	`ed.`	Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, December 8-13 2014, Montreal, Quebec, Canada NIPS Zoubin Ghahramani, Max Welling, Corinna Cortes, Neil D. Lawrence, Kilian Q. Weinberger
2014	A*	`conf`	Automatic Construction and Natural-Language Description of Nonparametric Regression Models. AAAI James Robert Lloyd, David Duvenaud, Roger B. Grosse, Joshua B. Tenenbaum, Zoubin Ghahramani
2014	J	`jnl`	Automatic Construction and Natural-Language Description of Nonparametric Regression Models. CoRR James Robert Lloyd, David Duvenaud, Roger B. Grosse, Joshua B. Tenenbaum, Zoubin Ghahramani
2014	A	`conf`	Avoiding pathologies in very deep networks. AISTATS David Duvenaud, Oren Rippel, Ryan P. Adams, Zoubin Ghahramani
2014	J	`jnl`	Avoiding pathologies in very deep networks. CoRR David Duvenaud, Oren Rippel, Ryan P. Adams, Zoubin Ghahramani
2014	A*	`conf`	Beta Diffusion Trees. ICML Creighton Heaukulani, David A. Knowles, Zoubin Ghahramani
2014	A*	`conf`	Cold-start Active Learning with Robust Ordinal Matrix Factorization. ICML Neil Houlsby, José Miguel Hernández-Lobato, Zoubin Ghahramani
2014	—	`conf`	Gaussian Process Volatility Model. NIPS Yue Wu, José Miguel Hernández-Lobato, Zoubin Ghahramani
2014	—	`conf`	General Table Completion using a Bayesian Nonparametric Model. NIPS Isabel Valera, Zoubin Ghahramani
2014	—	`ch.`	Partial Membership and Factor Analysis. Handbook of Mixed Membership Models and Their Applications Zoubin Ghahramani, Shakir Mohamed, Katherine A. Heller
2014	A*	`conf`	Pitfalls in the use of Parallel Inference for the Dirichlet Process. ICML Yarin Gal, Zoubin Ghahramani
2014	—	`conf`	Predictive Entropy Search for Efficient Global Optimization of Black-box Functions. NIPS José Miguel Hernández-Lobato, Matthew W. Hoffman, Zoubin Ghahramani
2014	J	`jnl`	Predictive Entropy Search for Efficient Global Optimization of Black-box Functions. CoRR José Miguel Hernández-Lobato, Matthew W. Hoffman, Zoubin Ghahramani
2014	A*	`conf`	Probabilistic Matrix Factorization with Non-random Missing Data. ICML José Miguel Hernández-Lobato, Neil Houlsby, Zoubin Ghahramani
2014	A*	`conf`	Randomized Nonlinear Component Analysis. ICML David Lopez-Paz, Suvrit Sra, Alexander J. Smola, Zoubin Ghahramani, Bernhard Schölkopf
2014	J	`jnl`	Randomized Nonlinear Component Analysis. CoRR David Lopez-Paz, Suvrit Sra, Alexander J. Smola, Zoubin Ghahramani, Bernhard Schölkopf
2014	A*	`conf`	Scalable Gaussian Process Structured Prediction for Grid Factor Graph Applications. ICML Sébastien Bratières, Novi Quadrianto, Sebastian Nowozin, Zoubin Ghahramani
2014	A*	`conf`	Stochastic Inference for Scalable Probabilistic Modeling of Binary Matrices. ICML José Miguel Hernández-Lobato, Neil Houlsby, Zoubin Ghahramani
2014	A	`conf`	Student-t Processes as Alternatives to Gaussian Processes. AISTATS Amar Shah, Andrew Gordon Wilson, Zoubin Ghahramani
2014	J	`jnl`	Student-t Processes as Alternatives to Gaussian Processes. CoRR Amar Shah, Andrew Gordon Wilson, Zoubin Ghahramani
2014	J	`jnl`	The Random Forest Kernel and other kernels for big data from random partitions. CoRR Alex Davies, Zoubin Ghahramani
2014	J	`jnl`	Warped Mixtures for Nonparametric Cluster Shapes. CoRR Tomoharu Iwata, David Duvenaud, Zoubin Ghahramani
2013	—	`conf`	A Generative Model of Vector Space Semantics. CVSM@ACL Jacob Andreas, Zoubin Ghahramani
2013	A	`conf`	Active Learning for Interactive Visualization. AISTATS Tomoharu Iwata, Neil Houlsby, Zoubin Ghahramani
2013	—	`ed.`	Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013, Lake Tahoe, Nevada, United States. NIPS Christopher J. C. Burges, Léon Bottou, Zoubin Ghahramani, Kilian Q. Weinberger
2013	J	`jnl`	Bayesian Structured Prediction Using Gaussian Processes. CoRR Sébastien Bratières, Novi Quadrianto, Zoubin Ghahramani
2013	A	`conf`	Determinantal Clustering Processes - A Nonparametric Bayesian Approach to Kernel Based Semi-Supervised Clustering. UAI Amar Shah, Zoubin Ghahramani
2013	J	`jnl`	Determinantal Clustering Processes - A Nonparametric Bayesian Approach to Kernel Based Semi-Supervised Clustering. CoRR Amar Shah, Zoubin Ghahramani
2013	A*	`conf`	Discovering latent influence in online social activities via shared cascade poisson processes. KDD Tomoharu Iwata, Amar Shah, Zoubin Ghahramani
2013	—	`conf`	Dynamic Covariance Models for Multivariate Financial Time Series. ICML (3) Yue Wu, José Miguel Hernández-Lobato, Zoubin Ghahramani
2013	—	`conf`	Dynamic Probabilistic Models for Latent Feature Propagation in Social Networks. ICML (1) Creighton Heaukulani, Zoubin Ghahramani
2013	—	`conf`	Gaussian Process Vine Copulas for Multivariate Dependence. ICML (2) David Lopez-Paz, José Miguel Hernández-Lobato, Zoubin Ghahramani
2013	J	`jnl`	Model Reductions for Inference: Generality of Pairwise, Binary, and Planar Factor Graphs. Neural Comput. Frederik Eaton, Zoubin Ghahramani
2013	A*	`conf`	SIGMa: simple greedy matching for aligning large knowledge bases. KDD Simon Lacoste-Julien, Konstantina Palla, Alex Davies, Gjergji Kasneci, Thore Graepel, Zoubin Ghahramani
2013	J	`jnl`	Scaling the Indian Buffet Process via Submodular Maximization CoRR Colorado Reed, Zoubin Ghahramani
2013	—	`conf`	Scaling the Indian Buffet Process via Submodular Maximization. ICML (3) Colorado Reed, Zoubin Ghahramani
2013	J	`jnl`	Structure Discovery in Nonparametric Regression through Compositional Kernel Search CoRR David Duvenaud, James Robert Lloyd, Roger B. Grosse, Joshua B. Tenenbaum, Zoubin Ghahramani
2013	—	`conf`	Structure Discovery in Nonparametric Regression through Compositional Kernel Search. ICML (3) David Duvenaud, James Robert Lloyd, Roger B. Grosse, Joshua B. Tenenbaum, Zoubin Ghahramani
2013	A	`conf`	The Supervised IBP: Neighbourhood Preserving Infinite Latent Feature Models. UAI Novi Quadrianto, Viktoriia Sharmanska, David A. Knowles, Zoubin Ghahramani
2013	J	`jnl`	The Supervised IBP: Neighbourhood Preserving Infinite Latent Feature Models. CoRR Novi Quadrianto, Viktoriia Sharmanska, David A. Knowles, Zoubin Ghahramani
2013	—	`conf`	Variational Hidden Conditional Random Fields with Coupled Dirichlet Process Mixtures. ECML/PKDD (2) Konstantinos Bousmalis, Stefanos Zafeiriou, Louis-Philippe Morency, Maja Pantic, Zoubin Ghahramani
2013	A	`conf`	Warped Mixtures for Nonparametric Cluster Shapes. UAI Tomoharu Iwata, David Duvenaud, Zoubin Ghahramani
2012	J	`jnl`	A Non-Parametric Bayesian Method for Inferring Hidden Causes. CoRR Frank D. Wood, Thomas L. Griffiths, Zoubin Ghahramani
2012	A	`conf`	A Nonparametric Bayesian Model for Multiple Clustering with Overlapping Feature Views. AISTATS Donglin Niu, Jennifer G. Dy, Zoubin Ghahramani
2012	—	`conf`	A nonparametric variable clustering model. NIPS David A. Knowles, Konstantina Palla, Zoubin Ghahramani
2012	—	`conf`	Active Learning of Model Evidence Using Bayesian Quadrature. NIPS Michael A. Osborne, David Duvenaud, Roman Garnett, Carl E. Rasmussen, Stephen J. Roberts, Zoubin Ghahramani
2012	A*	`conf`	An Infinite Latent Attribute Model for Network Data. ICML Konstantina Palla, David A. Knowles, Zoubin Ghahramani
2012	A	`conf`	Bayesian Classifier Combination. AISTATS Hyun-Chul Kim, Zoubin Ghahramani
2012	J	`jnl`	Bayesian Inference for Gaussian Mixed Graph Models. CoRR Ricardo Bezerra de Andrade e Silva, Zoubin Ghahramani
2012	J	`jnl`	Bayesian Learning in Undirected Graphical Models: Approximate MCMC algorithms CoRR Iain Murray, Zoubin Ghahramani
2012	J	`jnl`	Bayesian correlated clustering to integrate multiple datasets. Bioinform. Paul D. W. Kirk, Jim E. Griffin, Richard S. Savage, Zoubin Ghahramani, David L. Wild
2012	—	`conf`	Collaborative Gaussian Processes for Preference Learning. NIPS Neil Houlsby, José Miguel Hernández-Lobato, Ferenc Huszar, Zoubin Ghahramani
2012	—	`conf`	Continuous Relaxations for Discrete Hamiltonian Monte Carlo. NIPS Yichuan Zhang, Charles Sutton, Amos J. Storkey, Zoubin Ghahramani
2012	J	`jnl`	Copula-based Kernel Dependency Measures CoRR Barnabás Póczos, Zoubin Ghahramani, Jeff G. Schneider
2012	A*	`conf`	Copula-based Kernel Dependency Measures. ICML Barnabás Póczos, Zoubin Ghahramani, Jeff G. Schneider
2012	J	`jnl`	Correlated Non-Parametric Latent Feature Models CoRR Finale Doshi-Velez, Zoubin Ghahramani
2012	A*	`conf`	Evaluating Bayesian and L1 Approaches for Sparse Unsupervised Learning . ICML Shakir Mohamed, Katherine A. Heller, Zoubin Ghahramani
2012	A	`conf`	Flexible Martingale Priors for Deep Hierarchies. AISTATS Jacob Steinhardt, Zoubin Ghahramani
2012	A*	`conf`	Gaussian Process Regression Networks. ICML Andrew Gordon Wilson, David A. Knowles, Zoubin Ghahramani
2012	A	`conf`	Gaussian Processes for time-marked time-series data. AISTATS John P. Cunningham, Zoubin Ghahramani, Carl Edward Rasmussen
2012	—	`conf`	Modelling Input Varying Correlations between Multiple Responses. ECML/PKDD (2) Andrew Gordon Wilson, Zoubin Ghahramani
2012	J	`jnl`	On the Convergence of Bound Optimization Algorithms CoRR Ruslan Salakhutdinov, Sam T. Roweis, Zoubin Ghahramani
2012	—	`conf`	Random function priors for exchangeable arrays with applications to graphs and relational data. NIPS James Robert Lloyd, Peter Orbanz, Zoubin Ghahramani, Daniel M. Roy
2012	J	`jnl`	SiGMa: Simple Greedy Matching for Aligning Large Knowledge Bases CoRR Simon Lacoste-Julien, Konstantina Palla, Alex Davies, Gjergji Kasneci, Thore Graepel, Zoubin Ghahramani
2012	J	`jnl`	Variable noise and dimensionality reduction for sparse Gaussian processes. CoRR Edward Lloyd Snelson, Zoubin Ghahramani
2011	B	`conf`	A Comparison of Human and Agent Reinforcement Learning in Partially Observable Domains. CogSci Finale Doshi-Velez, Zoubin Ghahramani
2011	A	`conf`	Approximate inference for the loss-calibrated Bayesian. AISTATS Simon Lacoste-Julien, Ferenc Huszar, Zoubin Ghahramani
2011	J	`jnl`	Bayesian Active Learning for Classification and Preference Learning CoRR Neil Houlsby, Ferenc Huszar, Zoubin Ghahramani, Máté Lengyel
2011	J	`jnl`	Bayesian and L1 Approaches to Sparse Unsupervised Learning CoRR Shakir Mohamed, Katherine A. Heller, Zoubin Ghahramani
2011	J	`jnl`	Editor's Note. IEEE Trans. Pattern Anal. Mach. Intell. Ramin Zabih, Zoubin Ghahramani, Sing Bing Kang, Jiri Matas
2011	J	`jnl`	Editorial. IEEE Trans. Pattern Anal. Mach. Intell. Ramin Zabih, Zoubin Ghahramani, Sing Bing Kang, Jiri Matas
2011	A	`conf`	Generalised Wishart Processes. UAI Andrew Gordon Wilson, Zoubin Ghahramani
2011	A*	`conf`	Message Passing Algorithms for the Dirichlet Diffusion Tree. ICML David A. Knowles, Jurgen Van Gael, Zoubin Ghahramani
2011	A	`conf`	Pitman-Yor Diffusion Trees. UAI David A. Knowles, Zoubin Ghahramani
2011	J	`jnl`	State of the Journal. IEEE Trans. Pattern Anal. Mach. Intell. Ramin Zabih, Jiri Matas, Zoubin Ghahramani
2011	—	`conf`	Testing a Bayesian Measure of Representativeness Using a Large Image Database. NIPS Joshua T. Abbott, Katherine A. Heller, Zoubin Ghahramani, Thomas L. Griffiths
2011	—	`conf`	The Dynamic Beamformer. MLINI Ali Bahramisharif, Marcel A. J. van Gerven, Jan-Mathijs Schoffelen, Zoubin Ghahramani, Tom Heskes
2011	J	`jnl`	The Indian Buffet Process: An Introduction and Review. J. Mach. Learn. Res. Thomas L. Griffiths, Zoubin Ghahramani
2010	B	`conf`	(Invited Talk) Bayesian Hidden Markov Models and Extensions. CoNLL Zoubin Ghahramani
2010	J	`jnl`	A Robust Bayesian Two-Sample Test for Detecting Intervals of Differential Gene Expression in Microarray Time Series. J. Comput. Biol. Oliver Stegle, Katherine J. Denby, Emma J. Cooke, David L. Wild, Zoubin Ghahramani, Karsten M. Borgwardt
2010	—	`conf`	Copula Processes. NIPS Andrew Gordon Wilson, Zoubin Ghahramani
2010	A	`conf`	Dependent Indian Buffet Processes. AISTATS Sinead Williamson, Peter Orbanz, Zoubin Ghahramani
2010	J	`jnl`	Discovering transcriptional modules by Bayesian data integration. Bioinform. Richard S. Savage, Zoubin Ghahramani, Jim E. Griffin, Bernard J. de la Cruz, David L. Wild
2010	J	`jnl`	Editor's Note. IEEE Trans. Pattern Anal. Mach. Intell. Ramin Zabih, Jiri Matas, Zoubin Ghahramani
2010	J	`jnl`	Editor's Note. IEEE Trans. Pattern Anal. Mach. Intell. Ramin Zabih, Jiri Matas, Zoubin Ghahramani
2010	J	`jnl`	Editor's Note. IEEE Trans. Pattern Anal. Mach. Intell. Ramin Zabih, Jiri Matas, Zoubin Ghahramani
2010	J	`jnl`	Gene function prediction from synthetic lethality networks via ranking on demand. Bioinform. Christoph Lippert, Zoubin Ghahramani, Karsten M. Borgwardt
2010	J	`jnl`	Kronecker Graphs: An Approach to Modeling Networks. J. Mach. Learn. Res. Jure Leskovec, Deepayan Chakrabarti, Jon M. Kleinberg, Christos Faloutsos, Zoubin Ghahramani
2010	A	`conf`	Learning the Structure of Deep Sparse Graphical Models. AISTATS Ryan Prescott Adams, Hanna M. Wallach, Zoubin Ghahramani
2010	J	`jnl`	Nonparametric Bayesian Sparse Factor Models with application to Gene Expression modelling CoRR David A. Knowles, Zoubin Ghahramani
2010	B	`conf`	Probabilistic graphical models for semi-supervised traffic classification. IWCMC Charalampos Rotsos, Jurgen Van Gael, Andrew W. Moore, Zoubin Ghahramani
2010	C	`conf`	Scaling the iHMM: Parallelization versus Hadoop. CIT Sébastien Bratières, Jurgen Van Gael, Andreas Vlachos, Zoubin Ghahramani
2010	—	`conf`	Tree-Structured Stick Breaking for Hierarchical Data. NIPS Ryan Prescott Adams, Zoubin Ghahramani, Michael I. Jordan
2009	B	`conf`	A Robust Bayesian Two-Sample Test for Detecting Intervals of Differential Gene Expression in Microarray Time Series. RECOMB Oliver Stegle, Katherine J. Denby, David L. Wild, Zoubin Ghahramani, Karsten M. Borgwardt
2009	A	`conf`	A kernel method for unsupervised structured network inference. AISTATS Christoph Lippert, Oliver Stegle, Zoubin Ghahramani, Karsten M. Borgwardt
2009	A*	`conf`	Accelerated sampling for the Indian Buffet Process. ICML Finale Doshi-Velez, Zoubin Ghahramani
2009	A*	`conf`	Archipelago: nonparametric Bayesian semi-supervised learning. ICML Ryan Prescott Adams, Zoubin Ghahramani
2009	J	`jnl`	Bayesian two-sample tests CoRR Karsten M. Borgwardt, Zoubin Ghahramani
2009	A	`conf`	Choosing a Variable to Clamp. AISTATS Frederik Eaton, Zoubin Ghahramani
2009	A	`conf`	Correlated Non-Parametric Latent Feature Models. UAI Finale Doshi-Velez, Zoubin Ghahramani
2009	—	`conf`	Discovering Temporal Patterns of Differential Gene Expression in Microarray Time Series. GCB Oliver Stegle, Katherine J. Denby, David L. Wild, Stuart McHattie, Andrew Meade, Zoubin Ghahramani, Karsten M. Borgwardt
2009	A	`conf`	Factorial Mixture of Gaussians and the Marginal Independence Model. AISTATS Ricardo Bezerra de Andrade e Silva, Zoubin Ghahramani
2009	J	`jnl`	Introduction of New Associate Editors. IEEE Trans. Pattern Anal. Mach. Intell. Ramin Zabih, Zoubin Ghahramani, Jiri Matas
2009	J	`jnl`	Introduction of New Associate Editors. IEEE Trans. Pattern Anal. Mach. Intell. Ramin Zabih, Jiri Matas, Zoubin Ghahramani
2009	—	`conf`	Large Scale Nonparametric Bayesian Inference: Data Parallelisation in the Indian Buffet Process. NIPS Finale Doshi-Velez, David A. Knowles, Shakir Mohamed, Zoubin Ghahramani
2009	J	`jnl`	Modeling and Visualizing Uncertainty in Gene Expression Clusters Using Dirichlet Process Mixtures. IEEE ACM Trans. Comput. Biol. Bioinform. Carl Edward Rasmussen, Bernard J. de la Cruz, Zoubin Ghahramani, David L. Wild
2009	A	`conf`	Probabilistic Models for Incomplete Multi-dimensional Arrays. AISTATS Wei Chu, Zoubin Ghahramani
2009	J	`jnl`	R/BHC: fast Bayesian hierarchical clustering for microarray data. BMC Bioinform. Richard S. Savage, Katherine A. Heller, Yang Xu, Zoubin Ghahramani, William M. Truman, Murray Grant, Katherine J. Denby, David L. Wild
2009	J	`jnl`	Ranking Relations using Analogies in Biological and Information Networks CoRR Ricardo Bezerra de Andrade e Silva, Katherine A. Heller, Zoubin Ghahramani, Edoardo M. Airoldi
2009	A	`conf`	The Block Diagonal Infinite Hidden Markov Model. AISTATS Thomas S. Stepleton, Zoubin Ghahramani, Geoffrey J. Gordon, Tai Sing Lee
2009	J	`jnl`	The Hidden Life of Latent Variables: Bayesian Learning with Mixed Graph Models. J. Mach. Learn. Res. Ricardo Bezerra de Andrade e Silva, Zoubin Ghahramani
2009	A*	`conf`	The infinite HMM for unsupervised PoS tagging. EMNLP Jurgen Van Gael, Andreas Vlachos, Zoubin Ghahramani
2009	A	`conf`	Tree-Based Inference for Dirichlet Process Mixtures. AISTATS Yang Xu, Katherine A. Heller, Zoubin Ghahramani
2008	—	`conf`	Bayesian Exponential Family PCA. NIPS Shakir Mohamed, Katherine A. Heller, Zoubin Ghahramani
2008	A	`conf`	Bayesian Methods for Artificial Intelligence and Machine Learning. ECAI Zoubin Ghahramani
2008	A*	`conf`	Beam sampling for the infinite hidden Markov model. ICML Jurgen Van Gael, Yunus Saatci, Yee Whye Teh, Zoubin Ghahramani
2008	J	`jnl`	Editorial-State of the Transactions. IEEE Trans. Pattern Anal. Mach. Intell. David J. Kriegman, David J. Fleet, Zoubin Ghahramani
2008	J	`jnl`	Flexible latent variable models for multi-task learning. Mach. Learn. Jian Zhang, Zoubin Ghahramani, Yiming Yang
2008	J	`jnl`	Introduction of New Associate Editors. IEEE Trans. Pattern Anal. Mach. Intell. David J. Kriegman, David J. Fleet, Zoubin Ghahramani
2008	J	`jnl`	Introduction of New Associate Editors. IEEE Trans. Pattern Anal. Mach. Intell. David J. Kriegman, David J. Fleet, Zoubin Ghahramani
2008	J	`jnl`	Introduction of New Associate Editors. IEEE Trans. Pattern Anal. Mach. Intell. David J. Kriegman, David J. Fleet, Zoubin Ghahramani
2008	J	`jnl`	Kronecker Graphs: An Approach to Modeling Networks. CoRR Jure Leskovec, Deepayan Chakrabarti, Jon M. Kleinberg, Christos Faloutsos, Zoubin Ghahramani
2008	J	`jnl`	Latent-Space Variational Bayes. IEEE Trans. Pattern Anal. Mach. Intell. Jaemo Sung, Zoubin Ghahramani, Sung Yang Bang
2008	A*	`conf`	Metropolis Algorithms for Representative Subgraph Sampling. ICDM Christian Hübler, Hans-Peter Kriegel, Karsten M. Borgwardt, Zoubin Ghahramani
2008	—	`conf`	Outlier Robust Gaussian Process Classification. SSPR/SPR Hyun-Chul Kim, Zoubin Ghahramani
2008	—	`conf`	Representative Subgraph Sampling using Markov Chain Monte Carlo Methods. MLG@ICML Christian Hübler, Karsten M. Borgwardt, Hans-Peter Kriegel, Zoubin Ghahramani
2008	J	`jnl`	Second-Order Latent-Space Variational Bayes for Approximate Bayesian Inference. IEEE Signal Process. Lett. Jaemo Sung, Zoubin Ghahramani, Sung Yang Bang
2008	A*	`conf`	Statistical models for partial membership. ICML Katherine A. Heller, Sinead Williamson, Zoubin Ghahramani
2008	—	`conf`	The Infinite Factorial Hidden Markov Model. NIPS Jurgen Van Gael, Yee Whye Teh, Zoubin Ghahramani
2007	A	`conf`	A Nonparametric Bayesian Approach to Modeling Overlapping Clusters. AISTATS Katherine A. Heller, Zoubin Ghahramani
2007	A	`conf`	Analogical Reasoning with Relational Bayesian Sets. AISTATS Ricardo Bezerra de Andrade e Silva, Katherine A. Heller, Zoubin Ghahramani
2007	—	`conf`	Hidden Common Cause Relations in Relational Learning. NIPS Ricardo Bezerra de Andrade e Silva, Wei Chu, Zoubin Ghahramani
2007	—	`conf`	Infinite Sparse Factor Analysis and Infinite Independent Components Analysis. ICA David A. Knowles, Zoubin Ghahramani
2007	A	`conf`	Local and global sparse Gaussian process approximations. AISTATS Edward Lloyd Snelson, Zoubin Ghahramani
2007	A*	`ed.`	Machine Learning, Proceedings of the Twenty-Fourth International Conference (ICML 2007), Corvallis, Oregon, USA, June 20-24, 2007 ICML Zoubin Ghahramani
2007	A	`conf`	Stick-breaking Construction for the Indian Buffet Process. AISTATS Yee Whye Teh, Dilan Görür, Zoubin Ghahramani
2006	A	`conf`	A Non-Parametric Bayesian Method for Inferring Hidden Causes. UAI Frank D. Wood, Thomas L. Griffiths, Zoubin Ghahramani
2006	—	`conf`	A Simple Bayesian Framework for Content-Based Image Retrieval. CVPR (2) Katherine A. Heller, Zoubin Ghahramani
2006	A*	`conf`	A new approach to data driven clustering. ICML Arik Azran, Zoubin Ghahramani
2006	J	`jnl`	Appearance-based gender classification with Gaussian processes. Pattern Recognit. Lett. Hyun-Chul Kim, Daijin Kim, Zoubin Ghahramani, Sung Yang Bang
2006	J	`jnl`	Bayesian Gaussian Process Classification with the EM-EP Algorithm. IEEE Trans. Pattern Anal. Mach. Intell. Hyun-Chul Kim, Zoubin Ghahramani
2006	A	`conf`	Bayesian Inference for Gaussian Mixed Graph Models. UAI Ricardo Bezerra de Andrade e Silva, Zoubin Ghahramani
2006	J	`jnl`	Bayesian Segmental Models with Multiple Sequence Alignment Profiles for Protein Secondary Structure and Contact Map Prediction. IEEE ACM Trans. Comput. Biol. Bioinform. Wei Chu, Zoubin Ghahramani, Alexei A. Podtelezhnikov, David L. Wild
2006	—	`ch.`	Bayesian Support Vector Machines for Feature Ranking and Selection. Feature Extraction Wei Chu, S. Sathiya Keerthi, Chong Jin Ong, Zoubin Ghahramani
2006	—	`conf`	Face Recognition Based on Separable Lattice HMMS. ICASSP (5) Daisuke Kurata, Yoshihiko Nankaku, Keiichi Tokuda, Tadashi Kitamura, Zoubin Ghahramani
2006	B	`conf`	Gender Classification with Bayesian Kernel Methods. IJCNN Hyun-Chul Kim, Daijin Kim, Zoubin Ghahramani, Sung Yang Bang
2006	—	`ch.`	Graph Kernels by Spectral Transforms. Semi-Supervised Learning Xiaojin Zhu, Jaz S. Kandola, John Lafferty, Zoubin Ghahramani
2006	Misc	`conf`	Identifying Protein Complexes in High-Throughput Protein Interaction Screens Using an Infinite Latent Feature Model. Pacific Symposium on Biocomputing Wei Chu, Zoubin Ghahramani, Roland Krause, David L. Wild
2006	A	`conf`	MCMC for Doubly-intractable Distributions. UAI Iain Murray, Zoubin Ghahramani, David J. C. MacKay
2006	—	`conf`	Modeling Dyadic Data with Binary Latent Factors. NIPS Edward Meeds, Zoubin Ghahramani, Radford M. Neal, Sam T. Roweis
2006	—	`conf`	Relational Learning with Gaussian Processes. NIPS Wei Chu, Vikas Sindhwani, Zoubin Ghahramani, S. Sathiya Keerthi
2006	—	`conf`	Spectral Methods for Automatic Multiscale Data Clustering. CVPR (1) Arik Azran, Zoubin Ghahramani
2006	A	`conf`	Variable Noise and Dimensionality Reduction for Sparse Gaussian processes. UAI Edward Lloyd Snelson, Zoubin Ghahramani
2005	J	`jnl`	A Bayesian approach to reconstructing genetic regulatory networks with hidden factors. Bioinform. Matthew J. Beal, Francesco Falciani, Zoubin Ghahramani, Claudia Rangel, David L. Wild
2005	—	`conf`	Bayesian Sets. NIPS Zoubin Ghahramani, Katherine A. Heller
2005	A*	`conf`	Bayesian hierarchical clustering. ICML Katherine A. Heller, Zoubin Ghahramani
2005	J	`jnl`	Biomarker discovery in microarray gene expression data with Gaussian processes. Bioinform. Wei Chu, Zoubin Ghahramani, Francesco Falciani, David L. Wild
2005	A*	`conf`	Compact approximations to Bayesian predictive distributions. ICML Edward Lloyd Snelson, Zoubin Ghahramani
2005	J	`jnl`	Gaussian Processes for Ordinal Regression. J. Mach. Learn. Res. Wei Chu, Zoubin Ghahramani
2005	—	`conf`	Infinite latent feature models and the Indian buffet process. NIPS Thomas L. Griffiths, Zoubin Ghahramani
2005	—	`conf`	Learning Multiple Related Tasks using Latent Independent Component Analysis. NIPS Jian Zhang, Zoubin Ghahramani, Yiming Yang
2005	—	`conf`	Nested sampling for Potts models. NIPS Iain Murray, David J. C. MacKay, Zoubin Ghahramani, John Skilling
2005	A*	`conf`	Preference learning with Gaussian processes. ICML Wei Chu, Zoubin Ghahramani
2005	A	`ed.`	Proceedings of the Tenth International Workshop on Artificial Intelligence and Statistics, AISTATS 2005, Bridgetown, Barbados, January 6-8, 2005 AISTATS Robert G. Cowell, Zoubin Ghahramani
2005	—	`conf`	Sparse Gaussian Processes using Pseudo-inputs. NIPS Edward Lloyd Snelson, Zoubin Ghahramani
2005	—	`conf`	U-Likelihood and U-Updating Algorithms: Statistical Inference in Latent Variable Models. ECML Jaemo Sung, Sung Yang Bang, Seungjin Choi, Zoubin Ghahramani
2004	—	`conf`	A Probabilistic Model for Online Document Clustering with Application to Novelty Detection. NIPS Jian Zhang, Zoubin Ghahramani, Yiming Yang
2004	A*	`conf`	A graphical model for protein secondary structure prediction. ICML Wei Chu, Zoubin Ghahramani, David L. Wild
2004	A	`conf`	Bayesian Learning in Undirected Graphical Models: Approximate MCMC Algorithms. UAI Iain Murray, Zoubin Ghahramani
2004	Misc	`conf`	Clustering Protein Sequence and Structure Space with Infinite Gaussian Mixture Models. Pacific Symposium on Biocomputing Ananya Dubey, Seungwoo Hwang, Claudia Rangel, Carl Edward Rasmussen, Zoubin Ghahramani, David L. Wild
2004	J	`jnl`	Modeling T-cell activation using gene expression profiling and state-space models. Bioinform. Claudia Rangel, John Angus, Zoubin Ghahramani, Maria Lioumi, Elizabeth Sotheran, Alessia Gaiba, David L. Wild, Francesco Falciani
2004	—	`conf`	Nonparametric Transforms of Graph Kernels for Semi-Supervised Learning. NIPS Xiaojin Zhu, Jaz S. Kandola, Zoubin Ghahramani, John D. Lafferty
2004	A*	`conf`	Predictive automatic relevance determination by expectation propagation. ICML Yuan (Alan) Qi, Thomas P. Minka, Rosalind W. Picard, Zoubin Ghahramani
2004	B	`conf`	Protein secondary structure prediction using sigmoid belief networks to parameterize segmental semi-Markov models. ESANN Wei Chu, Zoubin Ghahramani, David L. Wild
2004	J	`jnl`	Simultaneous Localization and Mapping with Sparse Extended Information Filters. Int. J. Robotics Res. Sebastian Thrun, Yufeng Liu, Daphne Koller, Andrew Y. Ng, Zoubin Ghahramani, Hugh F. Durrant-Whyte
2004	Misc	`conf`	The Status of Structural Genomics Defined Through the Analysis of Current Targets and Structures. Pacific Symposium on Biocomputing Philip E. Bourne, C. K. J. Allerston, Werner G. Krebs, Wilfred W. Li, Ilya N. Shindyalov, Adam Godzik, Iddo Friedberg, Tong Liu, David L. Wild, Seungwoo Hwang, Zoubin Ghahramani, Li Chen, John D. Westbrook
2003	A	`conf`	On the Convergence of Bound Optimization Algorithms. UAI Ruslan Salakhutdinov, Sam T. Roweis, Zoubin Ghahramani
2003	A*	`conf`	Optimization with EM and Expectation-Conjugate-Gradient. ICML Ruslan Salakhutdinov, Sam T. Roweis, Zoubin Ghahramani
2003	A*	`conf`	Semi-Supervised Learning Using Gaussian Fields and Harmonic Functions. ICML Xiaojin Zhu, Zoubin Ghahramani, John D. Lafferty
2003	—	`conf`	Unsupervised Learning. Advanced Lectures on Machine Learning Zoubin Ghahramani
2003	—	`conf`	Warped Gaussian Processes. NIPS Edward Lloyd Snelson, Carl Edward Rasmussen, Zoubin Ghahramani
2002	J	`jnl`	A Bayesian network model for protein fold and remote homologue recognition. Bioinform. Alpan Raval, Zoubin Ghahramani, David L. Wild
2002	—	`conf`	Bayesian Monte Carlo. NIPS Carl Edward Rasmussen, Zoubin Ghahramani
2002	J	`jnl`	Bayesian model search for mixture models based on optimizing variational bounds. Neural Networks Naonori Ueda, Zoubin Ghahramani
2002	—	`conf`	Learning with Multiple Labels. NIPS Rong Jin, Zoubin Ghahramani
2002	C	`conf`	Simultaneous Mapping and Localization with Sparse Extended Information Filters: Theory and Initial Results. WAFR Sebastian Thrun, Daphne Koller, Zoubin Ghahramani, Hugh F. Durrant-Whyte, Andrew Y. Ng
2001	—	`ed.`	Advances in Neural Information Processing Systems 14 [Neural Information Processing Systems: Natural and Synthetic, NIPS 2001, December 3-8, 2001, Vancouver, British Columbia, Canada] NIPS Thomas G. Dietterich, Suzanna Becker, Zoubin Ghahramani
2001	J	`jnl`	An Introduction to Hidden Markov Models and Bayesian Networks. Int. J. Pattern Recognit. Artif. Intell. Zoubin Ghahramani
2001	—	`conf`	Infinite Mixtures of Gaussian Process Experts. NIPS Carl Edward Rasmussen, Zoubin Ghahramani
2001	—	`conf`	The Infinite Hidden Markov Model. NIPS Matthew J. Beal, Zoubin Ghahramani, Carl Edward Rasmussen
2000	B	`conf`	MFDTs: Mean Field Dynamic Trees. ICPR Nicholas J. Adams, Amos J. Storkey, Christopher K. I. Williams, Zoubin Ghahramani
2000	—	`conf`	Occam's Razor. NIPS Carl Edward Rasmussen, Zoubin Ghahramani
2000	—	`conf`	Propagation Algorithms for Variational Bayesian Learning. NIPS Zoubin Ghahramani, Matthew J. Beal
2000	J	`jnl`	SMEM Algorithm for Mixture Models. Neural Comput. Naonori Ueda, Ryohei Nakano, Zoubin Ghahramani, Geoffrey E. Hinton
2000	J	`jnl`	Split and Merge EM Algorithm for Improving Gaussian Mixture Density Estimates. J. VLSI Signal Process. Naonori Ueda, Ryohei Nakano, Zoubin Ghahramani, Geoffrey E. Hinton
2000	J	`jnl`	Variational Learning for Switching State-Space Models. Neural Comput. Zoubin Ghahramani, Geoffrey E. Hinton
1999	J	`jnl`	A Unifying Review of Linear Gaussian Models. Neural Comput. Sam T. Roweis, Zoubin Ghahramani
1999	J	`jnl`	An Introduction to Variational Methods for Graphical Models. Mach. Learn. Michael I. Jordan, Zoubin Ghahramani, Tommi S. Jaakkola, Lawrence K. Saul
1999	—	`conf`	Learning to Parse Images. NIPS Geoffrey E. Hinton, Zoubin Ghahramani, Yee Whye Teh
1999	—	`conf`	Variational Inference for Bayesian Mixtures of Factor Analysers. NIPS Zoubin Ghahramani, Matthew J. Beal
1998	—	`ch.`	A Hierarchical Community of Experts. Learning in Graphical Models Geoffrey E. Hinton, Brian Sallans, Zoubin Ghahramani
1998	—	`ch.`	An Introduction to Variational Methods for Graphical Models. Learning in Graphical Models Michael I. Jordan, Zoubin Ghahramani, Tommi S. Jaakkola, Lawrence K. Saul
1998	—	`conf`	Learning Nonlinear Dynamical Systems Using an EM Algorithm. NIPS Zoubin Ghahramani, Sam T. Roweis
1998	—	`conf`	SMEM Algorithm for Mixture Models. NIPS Naonori Ueda, Ryohei Nakano, Zoubin Ghahramani, Geoffrey E. Hinton
1997	J	`jnl`	Factorial Hidden Markov Models. Mach. Learn. Zoubin Ghahramani, Michael I. Jordan
1997	—	`conf`	Hierarchical Non-linear Factor Analysis and Topographic Maps. NIPS Zoubin Ghahramani, Geoffrey E. Hinton
1997	—	`conf`	Learning Dynamic Bayesian Networks. Summer School on Neural Networks Zoubin Ghahramani
1996	J	`jnl`	Active Learning with Statistical Models CoRR David A. Cohn, Zoubin Ghahramani, Michael I. Jordan
1996	J	`jnl`	Active Learning with Statistical Models. J. Artif. Intell. Res. David A. Cohn, Zoubin Ghahramani, Michael I. Jordan
1996	—	`conf`	Hidden Markov Decision Trees. NIPS Michael I. Jordan, Zoubin Ghahramani, Lawrence K. Saul
1995	—	`conf`	Factorial Hidden Markov Models. NIPS Zoubin Ghahramani, Michael I. Jordan
1994	—	`conf`	Active Learning with Statistical Models. NIPS David A. Cohn, Zoubin Ghahramani, Michael I. Jordan
1994	—	`conf`	Computational Structure of coordinate transformations: A generalization study. NIPS Zoubin Ghahramani, Daniel M. Wolpert, Michael I. Jordan
1994	—	`conf`	Factorial Learning and the EM Algorithm. NIPS Zoubin Ghahramani
1994	—	`conf`	Forward dynamic models in human motor control: Psychophysical evidence. NIPS Daniel M. Wolpert, Zoubin Ghahramani, Michael I. Jordan
1993	—	`conf`	Supervised learning from incomplete data via an EM approach. NIPS Zoubin Ghahramani, Michael I. Jordan