Supervised learning from incomplete data via an EM approach. - Zoubin Ghahramani; Michael I. Jordan (NIPS, 1993)

Factorial Learning and the EM Algorithm. - Zoubin Ghahramani (NIPS, 1994)

Computational Structure of coordinate transformations: A generalization study. - Zoubin Ghahramani; Daniel M. Wolpert; Michael I. Jordan (NIPS, 1994)

Forward dynamic models in human motor control: Psychophysical evidence. - Daniel M. Wolpert; Zoubin Ghahramani; Michael I. Jordan (NIPS, 1994)

Hidden Markov Decision Trees. - Michael I. Jordan; Zoubin Ghahramani; Lawrence K. Saul (NIPS, 1996)

Active Learning with Statistical Models. - David A. Cohn; Zoubin Ghahramani; Michael I. Jordan (J. Artif. Intell. Res., 1996)

Hierarchical Non-linear Factor Analysis and Topographic Maps. - Zoubin Ghahramani; Geoffrey E. Hinton (NIPS, 1997)

Learning Dynamic Bayesian Networks. - Zoubin Ghahramani (Summer School on Neural Networks, 1997)

Factorial Hidden Markov Models. - Zoubin Ghahramani; Michael I. Jordan (Mach. Learn., 1997)

A Hierarchical Community of Experts. - Geoffrey E. Hinton; Brian Sallans; Zoubin Ghahramani (Learning in Graphical Models, 1998)

An Introduction to Variational Methods for Graphical Models. - Michael I. Jordan; Zoubin Ghahramani; Tommi S. Jaakkola; Lawrence K. Saul (Learning in Graphical Models, 1998)

Learning Nonlinear Dynamical Systems Using an EM Algorithm. - Zoubin Ghahramani; Sam T. Roweis (NIPS, 1998)

Variational Inference for Bayesian Mixtures of Factor Analysers. - Zoubin Ghahramani; Matthew J. Beal (NIPS, 1999)

Learning to Parse Images. - Geoffrey E. Hinton; Zoubin Ghahramani; Yee Whye Teh (NIPS, 1999)

An Introduction to Variational Methods for Graphical Models. - Michael I. Jordan; Zoubin Ghahramani; Tommi S. Jaakkola; Lawrence K. Saul (Mach. Learn., 1999)

A Unifying Review of Linear Gaussian Models. - Sam T. Roweis; Zoubin Ghahramani (Neural Comput., 1999)

MFDTs: Mean Field Dynamic Trees. - Nicholas J. Adams; Amos J. Storkey; Christopher K. I. Williams; Zoubin Ghahramani (ICPR, 2000)

Propagation Algorithms for Variational Bayesian Learning. - Zoubin Ghahramani; Matthew J. Beal (NIPS, 2000)

Occam's Razor. - Carl Edward Rasmussen; Zoubin Ghahramani (NIPS, 2000)

Variational Learning for Switching State-Space Models. - Zoubin Ghahramani; Geoffrey E. Hinton (Neural Comput., 2000)

SMEM Algorithm for Mixture Models. - Naonori Ueda; Ryohei Nakano; Zoubin Ghahramani; Geoffrey E. Hinton (Neural Comput., 2000)

Split and Merge EM Algorithm for Improving Gaussian Mixture Density Estimates. - Naonori Ueda; Ryohei Nakano; Zoubin Ghahramani; Geoffrey E. Hinton (J. VLSI Signal Process., 2000)

The Infinite Hidden Markov Model. - Matthew J. Beal; Zoubin Ghahramani; Carl Edward Rasmussen (NIPS, 2001)

Infinite Mixtures of Gaussian Process Experts. - Carl Edward Rasmussen; Zoubin Ghahramani (NIPS, 2001)

An Introduction to Hidden Markov Models and Bayesian Networks. - Zoubin Ghahramani (Int. J. Pattern Recognit. Artif. Intell., 2001)

Learning with Multiple Labels. - Rong Jin 001; Zoubin Ghahramani (NIPS, 2002)

Bayesian Monte Carlo. - Carl Edward Rasmussen; Zoubin Ghahramani (NIPS, 2002)

Simultaneous Mapping and Localization with Sparse Extended Information Filters: Theory and Initial Results. - Sebastian Thrun; Daphne Koller; Zoubin Ghahramani; Hugh F. Durrant-Whyte; Andrew Y. Ng (WAFR, 2002)

A Bayesian network model for protein fold and remote homologue recognition. - Alpan Raval; Zoubin Ghahramani; David L. Wild (Bioinform., 2002)

Bayesian model search for mixture models based on optimizing variational bounds. - Naonori Ueda; Zoubin Ghahramani (Neural Networks, 2002)

Unsupervised Learning. - Zoubin Ghahramani (Advanced Lectures on Machine Learning, 2003)

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

Semi-Supervised Learning Using Gaussian Fields and Harmonic Functions. - Xiaojin Zhu 001; Zoubin Ghahramani; John D. Lafferty (ICML, 2003)

Warped Gaussian Processes. - Edward Lloyd Snelson; Carl Edward Rasmussen; Zoubin Ghahramani (NIPS, 2003)

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

Protein secondary structure prediction using sigmoid belief networks to parameterize segmental semi-Markov models. - Wei Chu; Zoubin Ghahramani; David L. Wild (ESANN, 2004)

A graphical model for protein secondary structure prediction. - Wei Chu; Zoubin Ghahramani; David L. Wild (ICML, 2004)

Predictive automatic relevance determination by expectation propagation. - Yuan (Alan) Qi; Thomas P. Minka; Rosalind W. Picard; Zoubin Ghahramani (ICML, 2004)

A Probabilistic Model for Online Document Clustering with Application to Novelty Detection. - Jian Zhang 003; Zoubin Ghahramani; Yiming Yang (NIPS, 2004)

Nonparametric Transforms of Graph Kernels for Semi-Supervised Learning. - Xiaojin Zhu 001; Jaz S. Kandola; Zoubin Ghahramani; John D. Lafferty (NIPS, 2004)

The Status of Structural Genomics Defined Through the Analysis of Current Targets and Structures. - 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 022; et al. (Pacific Symposium on Biocomputing, 2004)

Clustering Protein Sequence and Structure Space with Infinite Gaussian Mixture Models. - Ananya Dubey; Seungwoo Hwang; Claudia Rangel; Carl Edward Rasmussen; Zoubin Ghahramani; David L. Wild (Pacific Symposium on Biocomputing, 2004)

Bayesian Learning in Undirected Graphical Models: Approximate MCMC Algorithms. - Iain Murray 001; Zoubin Ghahramani (UAI, 2004)

Modeling T-cell activation using gene expression profiling and state-space models. - Claudia Rangel; John Angus; Zoubin Ghahramani; Maria Lioumi; Elizabeth Sotheran; Alessia Gaiba; David L. Wild; Francesco Falciani (Bioinform., 2004)

Simultaneous Localization and Mapping with Sparse Extended Information Filters. - Sebastian Thrun; Yufeng Liu; Daphne Koller; Andrew Y. Ng; Zoubin Ghahramani; Hugh F. Durrant-Whyte (Int. J. Robotics Res., 2004)

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

Preference learning with Gaussian processes. - Wei Chu; Zoubin Ghahramani (ICML, 2005)

Bayesian hierarchical clustering. - Katherine A. Heller; Zoubin Ghahramani (ICML, 2005)

Compact approximations to Bayesian predictive distributions. - Edward Lloyd Snelson; Zoubin Ghahramani (ICML, 2005)

Bayesian Sets. - Zoubin Ghahramani; Katherine A. Heller (NIPS, 2005)

Infinite latent feature models and the Indian buffet process. - Thomas L. Griffiths 001; Zoubin Ghahramani (NIPS, 2005)

Nested sampling for Potts models. - Iain Murray 001; David J. C. MacKay; Zoubin Ghahramani; John Skilling (NIPS, 2005)

Sparse Gaussian Processes using Pseudo-inputs. - Edward Lloyd Snelson; Zoubin Ghahramani (NIPS, 2005)

Learning Multiple Related Tasks using Latent Independent Component Analysis. - Jian Zhang 003; Zoubin Ghahramani; Yiming Yang (NIPS, 2005)

A Bayesian approach to reconstructing genetic regulatory networks with hidden factors. - Matthew J. Beal; Francesco Falciani; Zoubin Ghahramani; Claudia Rangel; David L. Wild (Bioinform., 2005)

Biomarker discovery in microarray gene expression data with Gaussian processes. - Wei Chu; Zoubin Ghahramani; Francesco Falciani; David L. Wild (Bioinform., 2005)

Gaussian Processes for Ordinal Regression. - Wei Chu; Zoubin Ghahramani (J. Mach. Learn. Res., 2005)

Graph Kernels by Spectral Transforms. - Xiaojin Zhu 001; Jaz S. Kandola; John Lafferty; Zoubin Ghahramani (Semi-Supervised Learning, 2006)

Bayesian Support Vector Machines for Feature Ranking and Selection. - Wei Chu; S. Sathiya Keerthi; Chong Jin Ong; Zoubin Ghahramani (Feature Extraction, 2006)

Spectral Methods for Automatic Multiscale Data Clustering. - Arik Azran; Zoubin Ghahramani (CVPR (1), 2006)

A Simple Bayesian Framework for Content-Based Image Retrieval. - Katherine A. Heller; Zoubin Ghahramani (CVPR (2), 2006)

Face Recognition Based on Separable Lattice HMMS. - Daisuke Kurata; Yoshihiko Nankaku; Keiichi Tokuda; Tadashi Kitamura; Zoubin Ghahramani (ICASSP (5), 2006)

A new approach to data driven clustering. - Arik Azran; Zoubin Ghahramani (ICML, 2006)

Gender Classification with Bayesian Kernel Methods. - Hyun-Chul Kim; Daijin Kim 001; Zoubin Ghahramani; Sung Yang Bang (IJCNN, 2006)

Relational Learning with Gaussian Processes. - Wei Chu; Vikas Sindhwani; Zoubin Ghahramani; S. Sathiya Keerthi (NIPS, 2006)

Modeling Dyadic Data with Binary Latent Factors. - Edward Meeds; Zoubin Ghahramani; Radford M. Neal; Sam T. Roweis (NIPS, 2006)

Identifying Protein Complexes in High-Throughput Protein Interaction Screens Using an Infinite Latent Feature Model. - Wei Chu; Zoubin Ghahramani; Roland Krause; David L. Wild (Pacific Symposium on Biocomputing, 2006)

MCMC for Doubly-intractable Distributions. - Iain Murray 001; Zoubin Ghahramani; David J. C. MacKay (UAI, 2006)

Bayesian Inference for Gaussian Mixed Graph Models. - Ricardo Bezerra de Andrade e Silva; Zoubin Ghahramani (UAI, 2006)

Variable Noise and Dimensionality Reduction for Sparse Gaussian processes. - Edward Lloyd Snelson; Zoubin Ghahramani (UAI, 2006)

A Non-Parametric Bayesian Method for Inferring Hidden Causes. - Frank D. Wood; Thomas L. Griffiths 001; Zoubin Ghahramani (UAI, 2006)

Bayesian Gaussian Process Classification with the EM-EP Algorithm. - Hyun-Chul Kim; Zoubin Ghahramani (IEEE Trans. Pattern Anal. Mach. Intell., 2006)

Appearance-based gender classification with Gaussian processes. - Hyun-Chul Kim; Daijin Kim 001; Zoubin Ghahramani; Sung Yang Bang (Pattern Recognit. Lett., 2006)

Bayesian Segmental Models with Multiple Sequence Alignment Profiles for Protein Secondary Structure and Contact Map Prediction. - Wei Chu; Zoubin Ghahramani; Alexei A. Podtelezhnikov; David L. Wild (IEEE ACM Trans. Comput. Biol. Bioinform., 2006)

Infinite Sparse Factor Analysis and Infinite Independent Components Analysis. - David A. Knowles; Zoubin Ghahramani (ICA, 2007)

Hidden Common Cause Relations in Relational Learning. - Ricardo Bezerra de Andrade e Silva; Wei Chu; Zoubin Ghahramani (NIPS, 2007)

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

Analogical Reasoning with Relational Bayesian Sets. - Ricardo Bezerra de Andrade e Silva; Katherine A. Heller; Zoubin Ghahramani (AISTATS, 2007)

Local and global sparse Gaussian process approximations. - Edward Lloyd Snelson; Zoubin Ghahramani (AISTATS, 2007)

Stick-breaking Construction for the Indian Buffet Process. - Yee Whye Teh; Dilan Görür; Zoubin Ghahramani (AISTATS, 2007)

Bayesian Methods for Artificial Intelligence and Machine Learning. - Zoubin Ghahramani (ECAI, 2008)

Metropolis Algorithms for Representative Subgraph Sampling. - Christian Hübler; Hans-Peter Kriegel; Karsten M. Borgwardt; Zoubin Ghahramani (ICDM, 2008)

Beam sampling for the infinite hidden Markov model. - Jurgen Van Gael; Yunus Saatci; Yee Whye Teh; Zoubin Ghahramani (ICML, 2008)

Statistical models for partial membership. - Katherine A. Heller; Sinead Williamson; Zoubin Ghahramani (ICML, 2008)

Representative Subgraph Sampling using Markov Chain Monte Carlo Methods. - Christian Hübler; Karsten M. Borgwardt; Hans-Peter Kriegel; Zoubin Ghahramani (MLG@ICML, 2008)

The Infinite Factorial Hidden Markov Model. - Jurgen Van Gael; Yee Whye Teh; Zoubin Ghahramani (NIPS, 2008)

Bayesian Exponential Family PCA. - Shakir Mohamed; Katherine A. Heller; Zoubin Ghahramani (NIPS, 2008)

Outlier Robust Gaussian Process Classification. - Hyun-Chul Kim; Zoubin Ghahramani (SSPR/SPR, 2008)

Flexible latent variable models for multi-task learning. - Jian Zhang 003; Zoubin Ghahramani; Yiming Yang (Mach. Learn., 2008)

Editorial-State of the Transactions. - David J. Kriegman; David J. Fleet; Zoubin Ghahramani (IEEE Trans. Pattern Anal. Mach. Intell., 2008)

Introduction of New Associate Editors. - David J. Kriegman; David J. Fleet; Zoubin Ghahramani (IEEE Trans. Pattern Anal. Mach. Intell., 2008)

Latent-Space Variational Bayes. - JaeMo Sung; Zoubin Ghahramani; Sung Yang Bang (IEEE Trans. Pattern Anal. Mach. Intell., 2008)

Second-Order Latent-Space Variational Bayes for Approximate Bayesian Inference. - JaeMo Sung; Zoubin Ghahramani; Sung Yang Bang (IEEE Signal Process. Lett., 2008)

The infinite HMM for unsupervised PoS tagging. - Jurgen Van Gael; Andreas Vlachos 001; Zoubin Ghahramani (EMNLP, 2009)

Discovering Temporal Patterns of Differential Gene Expression in Microarray Time Series. - Oliver Stegle; Katherine J. Denby; David L. Wild; Stuart McHattie; Andrew Meade; Zoubin Ghahramani; Karsten M. Borgwardt (GCB, 2009)

Archipelago: nonparametric Bayesian semi-supervised learning. - Ryan Prescott Adams; Zoubin Ghahramani (ICML, 2009)

Accelerated sampling for the Indian Buffet Process. - Finale Doshi-Velez; Zoubin Ghahramani (ICML, 2009)

Large Scale Nonparametric Bayesian Inference: Data Parallelisation in the Indian Buffet Process. - Finale Doshi-Velez; David A. Knowles; Shakir Mohamed; Zoubin Ghahramani (NIPS, 2009)

A Robust Bayesian Two-Sample Test for Detecting Intervals of Differential Gene Expression in Microarray Time Series. - Oliver Stegle; Katherine J. Denby; David L. Wild; Zoubin Ghahramani; Karsten M. Borgwardt (RECOMB, 2009)

Correlated Non-Parametric Latent Feature Models. - Finale Doshi-Velez; Zoubin Ghahramani (UAI, 2009)

R/BHC: fast Bayesian hierarchical clustering for microarray data. - Richard S. Savage; Katherine A. Heller; Yang Xu 023; Zoubin Ghahramani; William M. Truman; Murray Grant; Katherine J. Denby; David L. Wild (BMC Bioinform., 2009)

Bayesian two-sample tests - Karsten M. Borgwardt; Zoubin Ghahramani (CoRR, 2009)

Ranking Relations using Analogies in Biological and Information Networks - Ricardo Bezerra de Andrade e Silva; Katherine A. Heller; Zoubin Ghahramani; Edoardo M. Airoldi (CoRR, 2009)

Probabilistic Models for Incomplete Multi-dimensional Arrays. - Wei Chu; Zoubin Ghahramani (AISTATS, 2009)

Choosing a Variable to Clamp. - Frederik Eaton; Zoubin Ghahramani (AISTATS, 2009)

A kernel method for unsupervised structured network inference. - Christoph Lippert; Oliver Stegle; Zoubin Ghahramani; Karsten M. Borgwardt (AISTATS, 2009)

The Hidden Life of Latent Variables: Bayesian Learning with Mixed Graph Models. - Ricardo Bezerra de Andrade e Silva; Zoubin Ghahramani (J. Mach. Learn. Res., 2009)

Factorial Mixture of Gaussians and the Marginal Independence Model. - Ricardo Bezerra de Andrade e Silva; Zoubin Ghahramani (AISTATS, 2009)

The Block Diagonal Infinite Hidden Markov Model. - Thomas S. Stepleton; Zoubin Ghahramani; Geoffrey J. Gordon; Tai Sing Lee (AISTATS, 2009)

Tree-Based Inference for Dirichlet Process Mixtures. - Yang Xu 023; Katherine A. Heller; Zoubin Ghahramani (AISTATS, 2009)

Introduction of New Associate Editors. - Ramin Zabih; Zoubin Ghahramani; Jiri Matas (IEEE Trans. Pattern Anal. Mach. Intell., 2009)

Modeling and Visualizing Uncertainty in Gene Expression Clusters Using Dirichlet Process Mixtures. - Carl Edward Rasmussen; Bernard J. de la Cruz; Zoubin Ghahramani; David L. Wild (IEEE ACM Trans. Comput. Biol. Bioinform., 2009)

Scaling the iHMM: Parallelization versus Hadoop. - Sébastien Bratières; Jurgen Van Gael; Andreas Vlachos 001; Zoubin Ghahramani (CIT, 2010)

(Invited Talk) Bayesian Hidden Markov Models and Extensions. - Zoubin Ghahramani (CoNLL, 2010)

Probabilistic graphical models for semi-supervised traffic classification. - Charalampos Rotsos; Jurgen Van Gael; Andrew W. Moore 002; Zoubin Ghahramani (IWCMC, 2010)

Tree-Structured Stick Breaking for Hierarchical Data. - Ryan Prescott Adams; Zoubin Ghahramani; Michael I. Jordan (NIPS, 2010)

Copula Processes. - Andrew Gordon Wilson; Zoubin Ghahramani (NIPS, 2010)

Gene function prediction from synthetic lethality networks via ranking on demand. - Christoph Lippert; Zoubin Ghahramani; Karsten M. Borgwardt (Bioinform., 2010)

Discovering transcriptional modules by Bayesian data integration. - Richard S. Savage; Zoubin Ghahramani; Jim E. Griffin; Bernard J. de la Cruz; David L. Wild (Bioinform., 2010)

Nonparametric Bayesian Sparse Factor Models with application to Gene Expression modelling - David A. Knowles; Zoubin Ghahramani (CoRR, 2010)

A Robust Bayesian Two-Sample Test for Detecting Intervals of Differential Gene Expression in Microarray Time Series. - Oliver Stegle; Katherine J. Denby; Emma J. Cooke; David L. Wild; Zoubin Ghahramani; Karsten M. Borgwardt (J. Comput. Biol., 2010)

Learning the Structure of Deep Sparse Graphical Models. - Ryan Prescott Adams; Hanna M. Wallach; Zoubin Ghahramani (AISTATS, 2010)

Kronecker Graphs: An Approach to Modeling Networks. - Jure Leskovec; Deepayan Chakrabarti; Jon M. Kleinberg; Christos Faloutsos; Zoubin Ghahramani (J. Mach. Learn. Res., 2010)

Dependent Indian Buffet Processes. - Sinead Williamson; Peter Orbanz; Zoubin Ghahramani (AISTATS, 2010)

Editor's Note. - Ramin Zabih; Jiri Matas; Zoubin Ghahramani (IEEE Trans. Pattern Anal. Mach. Intell., 2010)

A Comparison of Human and Agent Reinforcement Learning in Partially Observable Domains. - Finale Doshi-Velez; Zoubin Ghahramani (CogSci, 2011)

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

Testing a Bayesian Measure of Representativeness Using a Large Image Database. - Joshua T. Abbott; Katherine A. Heller; Zoubin Ghahramani; Thomas L. Griffiths 001 (NIPS, 2011)

The Dynamic Beamformer. - Ali Bahramisharif; Marcel A. J. van Gerven; Jan-Mathijs Schoffelen; Zoubin Ghahramani; Tom Heskes (MLINI, 2011)

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

Generalised Wishart Processes. - Andrew Gordon Wilson; Zoubin Ghahramani (UAI, 2011)

Bayesian and L1 Approaches to Sparse Unsupervised Learning - Shakir Mohamed; Katherine A. Heller; Zoubin Ghahramani (CoRR, 2011)

Bayesian Active Learning for Classification and Preference Learning - Neil Houlsby; Ferenc Huszar; Zoubin Ghahramani; Máté Lengyel (CoRR, 2011)

The Indian Buffet Process: An Introduction and Review. - Thomas L. Griffiths 001; Zoubin Ghahramani (J. Mach. Learn. Res., 2011)

Approximate inference for the loss-calibrated Bayesian. - Simon Lacoste-Julien; Ferenc Huszar; Zoubin Ghahramani (AISTATS, 2011)

Editor's Note. - Ramin Zabih; Zoubin Ghahramani; Sing Bing Kang; Jiri Matas (IEEE Trans. Pattern Anal. Mach. Intell., 2011)

Editorial. - Ramin Zabih; Zoubin Ghahramani; Sing Bing Kang; Jiri Matas (IEEE Trans. Pattern Anal. Mach. Intell., 2011)

State of the Journal. - Ramin Zabih; Jiri Matas; Zoubin Ghahramani (IEEE Trans. Pattern Anal. Mach. Intell., 2011)

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

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

Copula-based Kernel Dependency Measures. - Barnabás Póczos; Zoubin Ghahramani; Jeff G. Schneider (ICML, 2012)

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

Collaborative Gaussian Processes for Preference Learning. - Neil Houlsby; José Miguel Hernández-Lobato; Ferenc Huszar; Zoubin Ghahramani (NIPS, 2012)

A nonparametric variable clustering model. - David A. Knowles; Konstantina Palla; Zoubin Ghahramani (NIPS, 2012)

Random function priors for exchangeable arrays with applications to graphs and relational data. - James Robert Lloyd; Peter Orbanz; Zoubin Ghahramani; Daniel M. Roy 001 (NIPS, 2012)

Active Learning of Model Evidence Using Bayesian Quadrature. - Michael A. Osborne; David Duvenaud; Roman Garnett; Carl E. Rasmussen; Stephen J. Roberts; Zoubin Ghahramani (NIPS, 2012)

Continuous Relaxations for Discrete Hamiltonian Monte Carlo. - Yichuan Zhang; Charles Sutton; Amos J. Storkey; Zoubin Ghahramani (NIPS, 2012)

Modelling Input Varying Correlations between Multiple Responses. - Andrew Gordon Wilson; Zoubin Ghahramani (ECML/PKDD (2), 2012)

Bayesian correlated clustering to integrate multiple datasets. - Paul D. W. Kirk; Jim E. Griffin; Richard S. Savage; Zoubin Ghahramani; David L. Wild (Bioinform., 2012)

Gaussian Processes for time-marked time-series data. - John P. Cunningham; Zoubin Ghahramani; Carl Edward Rasmussen (AISTATS, 2012)

Bayesian Classifier Combination. - Hyun-Chul Kim; Zoubin Ghahramani (AISTATS, 2012)

A Nonparametric Bayesian Model for Multiple Clustering with Overlapping Feature Views. - Donglin Niu; Jennifer G. Dy; Zoubin Ghahramani (AISTATS, 2012)

Flexible Martingale Priors for Deep Hierarchies. - Jacob Steinhardt; Zoubin Ghahramani (AISTATS, 2012)

A Generative Model of Vector Space Semantics. - Jacob Andreas; Zoubin Ghahramani (CVSM@ACL, 2013)

Active Learning for Interactive Visualization. - Tomoharu Iwata; Neil Houlsby; Zoubin Ghahramani (AISTATS, 2013)

Structure Discovery in Nonparametric Regression through Compositional Kernel Search. - David Duvenaud; James Robert Lloyd; Roger B. Grosse; Joshua B. Tenenbaum; Zoubin Ghahramani (ICML (3), 2013)

Dynamic Probabilistic Models for Latent Feature Propagation in Social Networks. - Creighton Heaukulani; Zoubin Ghahramani (ICML (1), 2013)

Gaussian Process Vine Copulas for Multivariate Dependence. - David Lopez-Paz; José Miguel Hernández-Lobato; Zoubin Ghahramani (ICML (2), 2013)

Scaling the Indian Buffet Process via Submodular Maximization. - Colorado Reed; Zoubin Ghahramani (ICML (3), 2013)

Dynamic Covariance Models for Multivariate Financial Time Series. - Yue Wu; José Miguel Hernández-Lobato; Zoubin Ghahramani (ICML (3), 2013)

Discovering latent influence in online social activities via shared cascade poisson processes. - Tomoharu Iwata; Amar Shah 001; Zoubin Ghahramani (KDD, 2013)

SIGMa: simple greedy matching for aligning large knowledge bases. - Simon Lacoste-Julien; Konstantina Palla; Alex Davies; Gjergji Kasneci; Thore Graepel; Zoubin Ghahramani (KDD, 2013)

Variational Hidden Conditional Random Fields with Coupled Dirichlet Process Mixtures. - Konstantinos Bousmalis; Stefanos Zafeiriou; Louis-Philippe Morency; Maja Pantic; Zoubin Ghahramani (ECML/PKDD (2), 2013)

Warped Mixtures for Nonparametric Cluster Shapes. - Tomoharu Iwata; David Duvenaud; Zoubin Ghahramani (UAI, 2013)

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

Determinantal Clustering Processes - A Nonparametric Bayesian Approach to Kernel Based Semi-Supervised Clustering. - Amar Shah 001; Zoubin Ghahramani (UAI, 2013)

Bayesian Structured Prediction Using Gaussian Processes. - Sébastien Bratières; Novi Quadrianto; Zoubin Ghahramani (CoRR, 2013)

Model Reductions for Inference: Generality of Pairwise, Binary, and Planar Factor Graphs. - Frederik Eaton; Zoubin Ghahramani (Neural Comput., 2013)

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

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

Avoiding pathologies in very deep networks. - David Duvenaud; Oren Rippel; Ryan P. Adams; Zoubin Ghahramani (AISTATS, 2014)

Student-t Processes as Alternatives to Gaussian Processes. - Amar Shah 001; Andrew Gordon Wilson; Zoubin Ghahramani (AISTATS, 2014)

Scalable Gaussian Process Structured Prediction for Grid Factor Graph Applications. - Sébastien Bratières; Novi Quadrianto; Sebastian Nowozin; Zoubin Ghahramani (ICML, 2014)

Pitfalls in the use of Parallel Inference for the Dirichlet Process. - Yarin Gal; Zoubin Ghahramani (ICML, 2014)

Beta Diffusion Trees. - Creighton Heaukulani; David A. Knowles; Zoubin Ghahramani (ICML, 2014)

Stochastic Inference for Scalable Probabilistic Modeling of Binary Matrices. - José Miguel Hernández-Lobato; Neil Houlsby; Zoubin Ghahramani (ICML, 2014)

Probabilistic Matrix Factorization with Non-random Missing Data. - José Miguel Hernández-Lobato; Neil Houlsby; Zoubin Ghahramani (ICML, 2014)

Cold-start Active Learning with Robust Ordinal Matrix Factorization. - Neil Houlsby; José Miguel Hernández-Lobato; Zoubin Ghahramani (ICML, 2014)

A reversible infinite HMM using normalised random measures. - David A. Knowles; Zoubin Ghahramani; Konstantina Palla (ICML, 2014)

Randomized Nonlinear Component Analysis. - David Lopez-Paz; Suvrit Sra; Alexander J. Smola; Zoubin Ghahramani; Bernhard Schölkopf (ICML, 2014)

Predictive Entropy Search for Efficient Global Optimization of Black-box Functions. - José Miguel Hernández-Lobato; Matthew W. Hoffman; Zoubin Ghahramani (NIPS, 2014)

General Table Completion using a Bayesian Nonparametric Model. - Isabel Valera; Zoubin Ghahramani (NIPS, 2014)

Gaussian Process Volatility Model. - Yue Wu; José Miguel Hernández-Lobato; Zoubin Ghahramani (NIPS, 2014)

The Random Forest Kernel and other kernels for big data from random partitions. - Alex Davies; Zoubin Ghahramani (CoRR, 2014)

Partial Membership and Factor Analysis. - Zoubin Ghahramani; Shakir Mohamed; Katherine A. Heller (Handbook of Mixed Membership Models and Their Applications, 2014)

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

Improving PPM with Dynamic Parameter Updates. - Christian Steinruecken; Zoubin Ghahramani; David J. C. MacKay (DCC, 2015)

Practical probabilistic programming with monads. - Adam Scibior; Zoubin Ghahramani; Andrew D. Gordon 001 (Haskell, 2015)

Latent Gaussian Processes for Distribution Estimation of Multivariate Categorical Data. - Yarin Gal; Yutian Chen 001; Zoubin Ghahramani (ICML, 2015)

Distributed Inference for Dirichlet Process Mixture Models. - Hong Ge; Yutian Chen 001; Moquan Wan; Zoubin Ghahramani (ICML, 2015)

A Probabilistic Model for Dirty Multi-task Feature Selection. - Daniel Hernández-Lobato; José Miguel Hernández-Lobato; Zoubin Ghahramani (ICML, 2015)

Predictive Entropy Search for Bayesian Optimization with Unknown Constraints. - José Miguel Hernández-Lobato; Michael A. Gelbart; Matthew W. Hoffman; Ryan P. Adams; Zoubin Ghahramani (ICML, 2015)

An Empirical Study of Stochastic Variational Inference Algorithms for the Beta Bernoulli Process. - Amar Shah 001; David A. Knowles; Zoubin Ghahramani (ICML, 2015)

Neural Adaptive Sequential Monte Carlo. - Shixiang Gu; Zoubin Ghahramani; Richard E. Turner (NIPS, 2015)

MCMC for Variationally Sparse Gaussian Processes. - James Hensman; Alexander G. de G. Matthews; Maurizio Filippone; Zoubin Ghahramani (NIPS, 2015)

Statistical Model Criticism using Kernel Two Sample Tests. - James Robert Lloyd; Zoubin Ghahramani (NIPS, 2015)

Parallel Predictive Entropy Search for Batch Global Optimization of Expensive Objective Functions. - Amar Shah 001; Zoubin Ghahramani (NIPS, 2015)

Particle Gibbs for Infinite Hidden Markov Models. - Nilesh Tripuraneni; Shixiang Gu; Hong Ge; Zoubin Ghahramani (NIPS, 2015)

Training generative neural networks via Maximum Mean Discrepancy optimization. - Gintare Karolina Dziugaite; Daniel M. Roy 001; Zoubin Ghahramani (UAI, 2015)

Subsampling-Based Approximate Monte Carlo for Discrete Distributions. - Yutian Chen 001; Zoubin Ghahramani (CoRR, 2015)

Bayesian Convolutional Neural Networks with Bernoulli Approximate Variational Inference. - Yarin Gal; Zoubin Ghahramani (CoRR, 2015)

Sandwiching the marginal likelihood using bidirectional Monte Carlo. - Roger B. Grosse; Zoubin Ghahramani; Ryan P. Adams (CoRR, 2015)

Slice Sampling for Probabilistic Programming. - Razvan Ranca; Zoubin Ghahramani (CoRR, 2015)

An Empirical Study of Stochastic Variational Algorithms for the Beta Bernoulli Process. - Amar Shah 001; David A. Knowles; Zoubin Ghahramani (CoRR, 2015)

Linear dimensionality reduction: survey, insights, and generalizations. - John P. Cunningham; Zoubin Ghahramani (J. Mach. Learn. Res., 2015)

Probabilistic machine learning and artificial intelligence. - Zoubin Ghahramani (Nat., 2015)

Variational Infinite Hidden Conditional Random Fields. - Konstantinos Bousmalis; Stefanos Zafeiriou; Louis-Philippe Morency; Maja Pantic; Zoubin Ghahramani (IEEE Trans. Pattern Anal. Mach. Intell., 2015)

GPstruct: Bayesian Structured Prediction Using Gaussian Processes. - Sébastien Bratières; Novi Quadrianto; Zoubin Ghahramani (IEEE Trans. Pattern Anal. Mach. Intell., 2015)

Pitman Yor Diffusion Trees for Bayesian Hierarchical Clustering. - David A. Knowles; Zoubin Ghahramani (IEEE Trans. Pattern Anal. Mach. Intell., 2015)

Relational Learning and Network Modelling Using Infinite Latent Attribute Models. - Konstantina Palla; David A. Knowles; Zoubin Ghahramani (IEEE Trans. Pattern Anal. Mach. Intell., 2015)

A Very Simple Safe-Bayesian Random Forest. - Novi Quadrianto; Zoubin Ghahramani (IEEE Trans. Pattern Anal. Mach. Intell., 2015)

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

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

Scalable Discrete Sampling as a Multi-Armed Bandit Problem. - Yutian Chen 001; Zoubin Ghahramani (ICML, 2016)

Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning. - Yarin Gal; Zoubin Ghahramani (ICML, 2016)

Pareto Frontier Learning with Expensive Correlated Objectives. - Amar Shah 001; Zoubin Ghahramani (ICML, 2016)

A Theoretically Grounded Application of Dropout in Recurrent Neural Networks. - Yarin Gal; Zoubin Ghahramani (NIPS, 2016)

Distributed Flexible Nonlinear Tensor Factorization. - Shandian Zhe; Kai Zhang 001; Pengyuan Wang 001; Kuang-chih Lee; Zenglin Xu; Yuan Qi 001; Zoubin Ghahramani (NIPS, 2016)

The Mondrian Kernel. - Matej Balog; Balaji Lakshminarayanan; Zoubin Ghahramani; Daniel M. Roy 001; Yee Whye Teh (UAI, 2016)

Markov Beta Processes for Time Evolving Dictionary Learning. - Amar Shah 001; Zoubin Ghahramani (UAI, 2016)

A study of the effect of JPG compression on adversarial images. - Gintare Karolina Dziugaite; Zoubin Ghahramani; Daniel M. Roy 001 (CoRR, 2016)

A General Framework for Constrained Bayesian Optimization using Information-based Search. - José Miguel Hernández-Lobato; Michael A. Gelbart; Ryan P. Adams; Matthew W. Hoffman; Zoubin Ghahramani (J. Mach. Learn. Res., 2016)

Unsupervised Many-to-Many Object Matching for Relational Data. - Tomoharu Iwata; James Robert Lloyd; Zoubin Ghahramani (IEEE Trans. Pattern Anal. Mach. Intell., 2016)

Human Activity Recognition by Combining a Small Number of Classifiers. - Alfredo Nazábal; Pablo Garcia-Moreno; Antonio Artés-Rodríguez; Zoubin Ghahramani (IEEE J. Biomed. Health Informatics, 2016)

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

Lost Relatives of the Gumbel Trick. - Matej Balog; Nilesh Tripuraneni; Zoubin Ghahramani; Adrian Weller (ICML, 2017)

Deep Bayesian Active Learning with Image Data. - Yarin Gal; Riashat Islam; Zoubin Ghahramani (ICML, 2017)

Bayesian inference on random simple graphs with power law degree distributions. - Juho Lee 001; Creighton Heaukulani; Zoubin Ghahramani; Lancelot F. James; Seungjin Choi (ICML, 2017)

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

Magnetic Hamiltonian Monte Carlo. - Nilesh Tripuraneni; Mark Rowland 001; Zoubin Ghahramani; Richard E. Turner (ICML, 2017)

Automatic Discovery of the Statistical Types of Variables in a Dataset. - Isabel Valera; Zoubin Ghahramani (ICML, 2017)

Interpolated Policy Gradient: Merging On-Policy and Off-Policy Gradient Estimation for Deep Reinforcement Learning. - Shixiang Gu; Tim Lillicrap; Richard E. Turner; Zoubin Ghahramani; Bernhard Schölkopf; Sergey Levine (NIPS, 2017)

One-Shot Learning in Discriminative Neural Networks. - Jordan Burgess; James Robert Lloyd; Zoubin Ghahramani (CoRR, 2017)

General Latent Feature Modeling for Data Exploration Tasks. - Isabel Valera; Melanie F. Pradier; Zoubin Ghahramani (CoRR, 2017)

GPflow: A Gaussian Process Library using TensorFlow. - Alexander G. de G. Matthews; Mark van der Wilk; Tom Nickson; Keisuke Fujii 002; Alexis Boukouvalas; Pablo León-Villagrá; Zoubin Ghahramani; James Hensman (J. Mach. Learn. Res., 2017)

Weakly Supervised Collective Feature Learning From Curated Media. - Yusuke Mukuta; Akisato Kimura; David B. Adrian; Zoubin Ghahramani (AAAI, 2018)

Turing: Composable inference for probabilistic programming. - Hong Ge; Kai Xu; Zoubin Ghahramani (AISTATS, 2018)

Few-shot learning of neural networks from scratch by pseudo example optimization. - Akisato Kimura; Zoubin Ghahramani; Koh Takeuchi 001; Tomoharu Iwata; Naonori Ueda (BMVC, 2018)

Gaussian Process Behaviour in Wide Deep Neural Networks. - Alexander G. de G. Matthews; Jiri Hron; Mark Rowland 001; Richard E. Turner; Zoubin Ghahramani (ICLR (Poster), 2018)

Discovering Interpretable Representations for Both Deep Generative and Discriminative Models. - Tameem Adel; Zoubin Ghahramani; Adrian Weller (ICML, 2018)

Variational Bayesian dropout: pitfalls and fixes. - Jiri Hron; Alexander G. de G. Matthews; Zoubin Ghahramani (ICML, 2018)

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

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

Branch-recombinant Gaussian processes for analysis of perturbations in biological time series. - Christopher A. Penfold; Anastasiya Sybirna; John E. Reid; Yun Huang; Lorenz Wernisch; Zoubin Ghahramani; Murray Grant; M. Azim Surani (Bioinform., 2018)

Imitation networks: Few-shot learning of neural networks from scratch. - Akisato Kimura; Zoubin Ghahramani; Koh Takeuchi 001; Tomoharu Iwata; Naonori Ueda (CoRR, 2018)

Variational Measure Preserving Flows. - Yichuan Zhang; José Miguel Hernández-Lobato; Zoubin Ghahramani (CoRR, 2018)

Probabilistic Deep Learning using Random Sum-Product Networks. - Robert Peharz; Antonio Vergari; Karl Stelzner; Alejandro Molina 001; Martin Trapp 001; Kristian Kersting; Zoubin Ghahramani (CoRR, 2018)

Probabilistic Meta-Representations Of Neural Networks. - Theofanis Karaletsos; Peter Dayan; Zoubin Ghahramani (CoRR, 2018)

Efficient and Robust Machine Learning for Real-World Systems. - Franz Pernkopf; Wolfgang Roth; Matthias Zöhrer; Lukas Pfeifenberger; Günther Schindler; Holger Fröning; Sebastian Tschiatschek; Robert Peharz; Matthew Mattina; Zoubin Ghahramani (CoRR, 2018)

Functional programming for modular Bayesian inference. - Adam Scibior; Ohad Kammar; Zoubin Ghahramani (Proc. ACM Program. Lang., 2018)

Denotational validation of higher-order Bayesian inference. - Adam Scibior; Ohad Kammar; Matthijs Vákár; Sam Staton; Hongseok Yang; Yufei Cai; Klaus Ostermann; Sean K. Moss; Chris Heunen; Zoubin Ghahramani (Proc. ACM Program. Lang., 2018)

The Automatic Statistician. - Christian Steinruecken; Emma Smith; David Janz; James Robert Lloyd; Zoubin Ghahramani (Automated Machine Learning, 2019)

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

Automatic Bayesian Density Analysis. - Antonio Vergari; Alejandro Molina 001; Robert Peharz; Zoubin Ghahramani; Kristian Kersting; Isabel Valera (AAAI, 2019)

AdvancedHMC.jl: A robust, modular and e cient implementation of advanced HMC algorithms. - Kai Xu; Hong Ge; Will Tebbutt; Mohamed Tarek; Martin Trapp 001; Zoubin Ghahramani (AABI, 2019)

Bayesian Learning of Sum-Product Networks. - Martin Trapp 001; Robert Peharz; Hong Ge; Franz Pernkopf; Zoubin Ghahramani (NeurIPS, 2019)

Random Sum-Product Networks: A Simple and Effective Approach to Probabilistic Deep Learning. - Robert Peharz; Antonio Vergari; Karl Stelzner; Alejandro Molina 001; Martin Trapp 001; Xiaoting Shao; Kristian Kersting; Zoubin Ghahramani (UAI, 2019)

Antithetic and Monte Carlo kernel estimators for partial rankings. - Maria Lomeli; Mark Rowland 001; Arthur Gretton; Zoubin Ghahramani (Stat. Comput., 2019)

Einsum Networks: Fast and Scalable Learning of Tractable Probabilistic Circuits. - Robert Peharz; Steven Lang; Antonio Vergari; Karl Stelzner; Alejandro Molina 001; Martin Trapp 001; Guy Van den Broeck; Kristian Kersting; Zoubin Ghahramani (ICML, 2020)

Resource-Efficient Neural Networks for Embedded Systems. - Wolfgang Roth; Günther Schindler; Matthias Zöhrer; Lukas Pfeifenberger; Robert Peharz; Sebastian Tschiatschek; Holger Fröning; Franz Pernkopf; Zoubin Ghahramani (CoRR, 2020)

DynamicPPL: Stan-like Speed for Dynamic Probabilistic Models. - Mohamed Tarek; Kai Xu; Martin Trapp 001; Hong Ge; Zoubin Ghahramani (CoRR, 2020)

Learning Continuous Treatment Policy and Bipartite Embeddings for Matching with Heterogeneous Causal Effects. - Will Y. Zou; Smitha Shyam; Michael Mui; Mingshi Wang; Jan O. Pedersen 001; Zoubin Ghahramani (CoRR, 2020)

General Latent Feature Models for Heterogeneous Datasets. - Isabel Valera; Melanie F. Pradier; Maria Lomeli; Zoubin Ghahramani (J. Mach. Learn. Res., 2020)

Handling incomplete heterogeneous data using VAEs. - Alfredo Nazábal; Pablo M. Olmos; Zoubin Ghahramani; Isabel Valera (Pattern Recognit., 2020)

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

Automatic prior selection for meta Bayesian optimization with a case study on tuning deep neural network optimizers. - Zi Wang; George E. Dahl; Kevin Swersky; Chansoo Lee; Zelda Mariet; Zachary Nado; Justin Gilmer; Jasper Snoek; Zoubin Ghahramani (CoRR, 2021)

Pre-training helps Bayesian optimization too. - Zi Wang; George E. Dahl; Kevin Swersky; Chansoo Lee; Zelda Mariet; Zachary Nado; Justin Gilmer; Jasper Snoek; Zoubin Ghahramani (CoRR, 2022)

Plex: Towards Reliability using Pretrained Large Model Extensions. - Dustin Tran; Jeremiah Z. Liu; Michael W. Dusenberry; Du Phan; Mark Collier; Jie Ren 006; Kehang Han; Zi Wang; Zelda Mariet; Huiyi Hu; Neil Band; Tim G. J. Rudner; et al. (CoRR, 2022)

Neural Diffusion Processes. - Vincent Dutordoir; Alan Saul; Zoubin Ghahramani; Fergus Simpson (ICML, 2023)

RecurrentGemma: Moving Past Transformers for Efficient Open Language Models. - 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; et al. (CoRR, 2024)

Towards Responsible Development of Generative AI for Education: An Evaluation-Driven Approach. - 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; et al. (CoRR, 2024)

Rethinking the Role of Bayesianism in the Age of Modern AI (Dagstuhl Seminar 24461). - Vincent Fortuin; Mohammad Emtiyaz Khan; Mark van der Wilk; Zoubin Ghahramani; Katharine Fisher (Dagstuhl Reports, 2024)

Resource-Efficient Neural Networks for Embedded Systems. - Wolfgang Roth; Günther Schindler; Bernhard Klein; Robert Peharz; Sebastian Tschiatschek; Holger Fröning; Franz Pernkopf; Zoubin Ghahramani (J. Mach. Learn. Res., 2024)

Pre-trained Gaussian Processes for Bayesian Optimization. - Zi Wang; George E. Dahl; Kevin Swersky; Chansoo Lee; Zachary Nado; Justin Gilmer; Jasper Snoek; Zoubin Ghahramani (J. Mach. Learn. Res., 2024)

Gemma 3 Technical Report. - Aishwarya Kamath; Johan Ferret; Shreya Pathak; Nino Vieillard; Ramona Merhej; Sarah Perrin; Tatiana Matejovicova; Alexandre Ramé; Morgane Rivière; Louis Rouillard; Thomas Mesnard; Geoffrey Cideron; et al. (CoRR, 2025)