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Research
I am interested in various aspects of Machine Learning
and Bayesian inference. It includes
deterministic approximate methods and
stochastic methods.
Here you'll find preprints, papers, talks and notes.
Publications
Acquisition of chess knowledge in AlphaZero
(PNAS,
arXiv)
Thomas McGrath, Andrei Kapishnikov, Nenad Tomašev, Adam Pearce, Martin Wattenberg, Demis Hassabis, Been Kim, Ulrich Paquet and Vladimir Kramnik
Proceedings of the National Academy of Sciences (PNAS), Vol. 119 No. 47, 2022
Efficient Bayesian inference of Instantaneous Reproduction Numbers at Fine Spatial Scales, with an Application to Mapping and Nowcasting the Covid-19 Epidemic in British Local Authorities
(Journal of the Royal Statistical Society Series A,
pdf)
Yee Whye Teh, Bryn Elesedy, Bobby He, Michael Hutchinson, Sheheryar Zaidi, Avishkar Bhoopchand, Ulrich Paquet, Nenad Tomašev, Jonathan Read, and Peter J. Diggle
Journal of the Royal Statistical Society Series A: Statistics in Society, Vol. 185, No. 2, Pages S65-S85, November 2022
Reimagining Chess with AlphaZero
(CACM,
pdf)
Nenad Tomašev, Ulrich Paquet, Demis Hassabis and Vladimir Kramnik
Communications of the ACM, Vol. 65 No. 2, Pages 60-66, February 2022
Role of Human-AI Interaction in Selective Prediction
(arXiv,
pdf)
Elizabeth Bondi, Raphael Koster, Hannah Sheahan, Martin Chadwick, Yoram Bachrach, Taylan Cemgil, Ulrich Paquet and Krishnamurthy Dvijotham
arXiv:2112.06751, 2021
The 36th AAAI Conference on Artificial Intelligence, 2022
Acquisition of Chess Knowledge in AlphaZero
(arXiv,
pdf)
Thomas McGrath, Andrei Kapishnikov, Nenad Tomašev, Adam Pearce, Demis Hassabis, Been Kim, Ulrich Paquet and Vladimir Kramnik
arXiv:2111.09259, 2021
Data Readiness: Lessons from an Emergency
(report)
The DELVE Initiative
DELVE Report No. 7. Published 24 November 2020
Organisational Data Maturity
(addendum)
Neil D. Lawrence, Jessica Montgomery and Ulrich Paquet
DELVE Addendum DATA-TD1. Published 24 November 2020
Assessing Game Balance with AlphaZero: Exploring Alternative Rule Sets in Chess
(arXiv,
pdf)
Nenad Tomašev, Ulrich Paquet, Demis Hassabis and Vladimir Kramnik
arXiv:2009.04374, 2020
Unsupervised Separation of Dynamics from Pixels
(arXiv,
pdf,
Metron)
Silvia Chiappa and Ulrich Paquet
Metron, Volume 77, 119-135, 2019
A Factorial Mixture Prior for Compositional Deep Generative Models
(arXiv,
pdf)
Ulrich Paquet, Sumedh K. Ghaisas and Olivier Tieleman
arXiv:1812.07480, 2018
Recurrent Relational Networks
(arXiv,
pdf)
Rasmus Berg Palm, Ulrich Paquet and Ole Winther
Advances in Neural Information Processing Systems 31, 2018
arXiv:1711.08028, 2017
Comparing Interpretable Inference Models for Videos of Physical Motion
(pdf)
Michael Pearce, Silvia Chiappa and Ulrich Paquet
Symposium on Advances in Approximate Bayesian Inference, 2018
A Disentangled Recognition and Nonlinear Dynamics Model for Unsupervised Learning
(arXiv,
pdf)
Marco Fraccaro, Simon Kamronn, Ulrich Paquet and Ole Winther
Advances in Neural Information Processing Systems 30, 2017
arXiv:1710.05741, 2017
Low-Rank Factorization of Determinantal Point Processes for Recommendation
(arXiv,
pdf,
AAAI pdf)
Mike Gartrell, Ulrich Paquet and Noam Koenigstein
The 31st AAAI Conference on Artificial Intelligence, 2017
arXiv:1602.05436, 2016
Knowing What to Ask: A Bayesian Active Learning Approach to the Surveying Problem
(pdf)
Yoad Lewenberg, Yoram Bachrach, Ulrich Paquet and Jeffrey S. Rosenschein
The 31st AAAI Conference on Artificial Intelligence, 2017
Groove Radio: A Bayesian Hierarchical Model for Personalized Playlist Generation
(pdf)
Shay Ben Elazar, Gal Lavee, Noam Koenigstein, Oren Barkan, Hilik Berezin, Ulrich Paquet and Tal Zaccai
WSDM, 2017
Sequential Neural Models with Stochastic Layers
(arXiv,
pdf,
NIPS version,
video)
(NIPS 2016 oral paper)
Marco Fraccaro, Søren Kaae Sønderby, Ulrich Paquet and Ole Winther
Advances in Neural Information Processing Systems 29, 2016
arXiv:1605.07571, 2016
An Adaptive Resample-Move Algorithm for Estimating Normalizing Constants
(arXiv,
pdf)
Marco Fraccaro, Ulrich Paquet and Ole Winther
arXiv:1604.01972, 2016
An Efficient Implementation of Riemannian Manifold Hamiltonian Monte Carlo for Gaussian Process Models
(pdf)
Ulrich Paquet and Marco Fraccaro
Supplementary material to arXiv:1604.01972, 2016
Bayesian Low-Rank Determinantal Point Processes
(pdf)
Mike Gartrell, Ulrich Paquet and Noam Koenigstein
RecSys '16 Proceedings of the tenth ACM conference on Recommender Systems, 2016
Beyond Collaborative Filtering: The List Recommendation Problem
(pdf)
Oren Sar Shalom, Noam Koenigstein, Ulrich Paquet and Hastagiri Vanchinathan
Proceedings of the 25th international conference on World Wide Web, 2016
Indexable Probabilistic Matrix Factorization for Maximum Inner Product Search
(pdf)
Marco Fraccaro, Ulrich Paquet and Ole Winther
The Thirtieth AAAI Conference on Artificial Intelligence, 2016
Collective Noise Contrastive Estimation for Policy Transfer Learning
(pdf,
MSRC link,
supplementary material,
poster)
Weinan Zhang, Ulrich Paquet and Katja Hofmann
The Thirtieth AAAI Conference on Artificial Intelligence, 2016
Perturbation Theory for Variational Inference
(pdf)
Manfred Opper, Marco Fraccaro, Ulrich Paquet, Alex Susemihl, and Ole Winther
NIPS 2015 Workshop on Advances in Approximate Bayesian Inferences, 2015
On the Convergence of Stochastic Variational Inference in Bayesian Networks
(pdf)
Ulrich Paquet
NIPS 2014 Workshop on Advances in Variational Inference, 2014
A Scalable Bayesian Alternative to Density Estimation with a Bilinear Softmax Function
(pdf)
Ulrich Paquet, Noam Koenigstein, and Ole Winther
NIPS 2014 Workshop on Personalization: Methods and Applications, 2014
Scalable Bayesian Modelling of Paired Symbols
(arXiv, pdf)
Ulrich Paquet, Noam Koenigstein, and Ole Winther
arXiv:1409.2824, 2014
Speeding Up the Xbox Recommender System Using a Euclidian Transformation for Inner Product Spaces
(pdf)
Yoram Bachrach, Yehuda Finkelstein, Ran Gilad-Bachrach, Liran Katzir, Noam Koenigstein, Nir Nice, and Ulrich Paquet
RecSys '14 Proceedings of the eighth ACM conference on Recommender Systems, 2014
A Large-scale Exploration of Group Viewing Patterns
(pdf)
best paper runner-up
Allison J.B. Chaney, Mike Gartrell, Jake M. Hofman, John Guiver, Noam Koenigstein, Pushmeet Kohli, and Ulrich Paquet
TVX 2014: ACM International Conference on Interactive Experiences for Television and Online Video, 2014
Mining Large-scale TV Group Viewing Patterns for Group Recommendation
(MSRC,
pdf)
Allison Chaney, Mike Gartrell, Jake Hofman, John Guiver, Noam Koenigstein, Pushmeet Kohli, and Ulrich Paquet
Microsoft Technical Report, Number MSR-TR-2013-114, 2013
[Favourite paper]
Perturbative Corrections for Approximate Inference in Gaussian Latent Variable Models
(arXiv,
JMLR,
pdf)
Manfred Opper, Ulrich Paquet, and Ole Winther
Journal of Machine Learning Research, Volume 14, 2857-2898, 2013
Xbox Movies Recommendations: Variational Bayes Matrix Factorization with Embedded Feature Selection
(pdf)
Noam Koenigstein and Ulrich Paquet
RecSys '13 Proceedings of the seventh ACM conference on Recommender Systems, 2013
One-class Collaborative Filtering with Random Graphs: Annotated Version
(arXiv, pdf)
Ulrich Paquet and Noam Koenigstein
arXiv:1309.6786, 2013
This arXiv version includes additional annotations to clarify some sections in the WWW 2013 paper.
One-class Collaborative Filtering with Random Graphs
(pdf correcting eq. 9)
Ulrich Paquet and Noam Koenigstein
Proceedings of the 22nd international conference on World Wide Web, 999-1008, 2013
[Video]
A preliminary talk, Large Scale Recommender System for The One Class Problem,
from the Workshop on Large-scale Online Learning and Decision Making (Cumberland Lodge 2012),
can be found here.
The Xbox Recommender System
(pdf)
Noam Koenigstein, Nir Nice, Ulrich Paquet, and Nir Schleyen
RecSys '12 Proceedings of the sixth ACM conference on Recommender Systems, 281-284, 2012
Collaborative Learning of Preference Rankings
(pdf)
Tim Salimans, Ulrich Paquet, and Thore Graepel
RecSys '12 Proceedings of the sixth ACM conference on Recommender Systems, 261-264, 2012
Transparent User Models for Personalization
(pdf, appendix, talk)
Khalid El-Arini, Ulrich Paquet, Ralf Herbrich, Jurgen Van Gael and Blaise Agüera y Arcas
Proc. of 18th International Conference on Knowledge Discovery and Data Mining (KDD 2012), 2012
A Bayesian Treatment of Social Links in Recommender Systems
(pdf)
Mike Gartrell, Ulrich Paquet, and Ralf Herbrich
Technical Report CU-CS-1092-12, University of Colorado, 2012
A Hierarchical Model for Ordinal Matrix Factorization
(preprint pdf; final publication available at
www.springerlink.com)
Ulrich Paquet, Blaise Thomson, and Ole Winther
Statistics and Computing, Volume 22(4), 945-957, 2012
Website and code: cogsys.imm.dtu.dk/ordinalmatrixfactorization;
video (NIPS workshop 2007)
A penny for your thoughts? The value of information in recommendation systems
(pdf)
Alexandre Passos, Jurgen Van Gael, Ralf Herbrich, and Ulrich Paquet
NIPS 2011 Workshop on Bayesian Optimization, Experimental Design, and Bandits, Sierra Nevada, Spain, 2011
Cumulant expansions for improved inference with EP in discrete Bayesian networks
(pdf)
Manfred Opper, Ulrich Paquet, and Ole Winther
3rd NIPS Workshop on Discrete Optimization in Machine Learning, Sierra Nevada, Spain, 2011
Vuvuzelas & Active Learning for Online Classification
(pdf)
Ulrich Paquet, Jurgen van Gael, David Stern, Gjergji Kasneci, Ralf Herbrich, and Thore Graepel
Computational Social Science and the Wisdom of Crowds Workshop (colocated with NIPS 2010), 2010
Large-scale Ordinal Collaborative Filtering
(pdf)
Ulrich Paquet, Blaise Thomson, and Ole Winther
1st Workshop on Mining the Future Internet, Future Internet Symposium, Berlin, September 2010
Perturbation Corrections in Approximate Inference: Mixture Modelling Applications
(JMLR,
pdf)
Ulrich Paquet, Manfred Opper, and Ole Winther
Journal of Machine Learning Research, Volume 10, 935-976, 2009
Convexity and Bayesian Constrained Local Models
(pdf)
Ulrich Paquet
CVPR (Computer Vision and Pattern Recognition) 2009
This paper contains ideas useful for face recognition. A summary
poster is also available.
Improving on Expectation Propagation
(pdf)
Manfred Opper, Ulrich Paquet, and Ole Winther
Advances in Neural Information Processing Systems 21, 1241-1248, 2009
Gaussian Process Modeling for Image Distortion Correction in EPI
Joseph W. Stevick, Sally G. Harding, Ulrich Paquet, Richard E. Ansorge, T. Adrian Carpenter, and Guy B. Williams
Magnetic Resonance in Medicine, Volume 59(3), 598-606, 2008
Bayesian Inference for Latent Variable Models
(pdf)
Ulrich Paquet
PhD Thesis. Computer Laboratory, University of Cambridge, 2007
Gaussian Process Modeling for EPI Distortion Correction
(pdf)
Joseph .W. Stevick, Sally G. Harding, Ulrich Paquet, Richard E. Ansorge, T. Adrian Carpenter, and Guy B. Williams
Joint Annual Meeting ISMRM-ESMRMB, 2007
Bayesian Hierarchical Ordinal Regression
(pdf, ps)
Ulrich Paquet, Sean Holden, and Andrew Naish-Guzman
Proceedings of the International Conference on Artificial Neural Networks, 2005
On The Explicit Use Of Example Weights In The Construction Of Classifiers
(pdf, ps)
Andrew Naish-Guzman, Sean Holden, and Ulrich Paquet
Proceedings of the International Conference on Artificial Neural Networks, 2005
Particle Swarms for Linearly Constrained Optimisation
Ulrich Paquet and Andries P. Engelbrecht
Fundamenta Informaticae, 76(1-2), 147-170, 2007
A New Particle Swarm Optimiser for Linearly Constrained Optimisation
(pdf)
Ulrich Paquet and Andries P. Engelbrecht
Proceedings of the Congress on Evolutionary Computation, pages 227-233, 2003
Training Support Vector Machines with Particle Swarms
(pdf)
Ulrich Paquet and Andries P. Engelbrecht
Proceedings of the International Joint Conference on Neural Networks, 2003
Training Support Vector Machines with Particle Swarms
(pdf, ps)
Ulrich Paquet
MSc Thesis. Department of Computer Science, University of Pretoria, 2003
Talks and various notes
[Video]
Large Scale Recommender System for The One Class Problem
(video)
Ulrich Paquet, with Noam Koenigstein and the Xbox Recommendations team
Workshop on Large-scale Online Learning and Decision Making, 2012
[Video]
Social recommender systems: a graphical model based approach
(video)
Jurgen van Gael, with Stuart Elmore, Ralf Herbrich, Allen Jones, Ulrich Paquet, and David Stern.
PASCAL International Workshop on Social Web Mining, 2011
This describes Project Emporia, a fun news recommendation engine based on Twitter.
This was our largest project at FUSE Labs
at Microsoft Research Cambridge.
[Video]
Large-scale Bayesian Inference for Collaborative Filtering
(video,
slides)
Ole Winther, with Ulrich Paquet, and Blaise Thomson
NIPS Workshop on Approximate Bayesian Inference in Continuous/Hybrid Models, 2007
[Video]
Improving on Expectation Propagation
(video,
slides,
poster)
Ulrich Paquet, with Ole Winther and Manfred Opper
NIPS Workshop on Approximate Bayesian Inference in Continuous/Hybrid Models, 2007
[Video]
Perturbative Corrections to Expectation Consistent Approximate Inference
(video,
slides)
Manfred Opper, with Ulrich Paquet and Ole Winther
NIPS Workshop on Approximate Bayesian Inference in Continuous/Hybrid Models, 2007
Empirical Bayesian Change Point Detection
(pdf)
Ulrich Paquet
2007
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