A new particle swarm optimiser for linearly constrained optimisation. - Ulrich Paquet; Andries P. Engelbrecht (IEEE Congress on Evolutionary Computation, 2003)

Training support vector machines with particle swarms. - Ulrich Paquet; Andries Petrus Engelbrecht (IJCNN, 2003)

On the Explicit Use of Example Weights in the Construction of Classifiers. - Andrew Naish-Guzman; Sean B. Holden; Ulrich Paquet (ICANN (2), 2005)

Bayesian Hierarchical Ordinal Regression. - Ulrich Paquet; Sean B. Holden; Andrew Naish-Guzman (ICANN (2), 2005)

Particle Swarms for Linearly Constrained Optimisation. - Ulrich Paquet; Andries P. Engelbrecht (Fundam. Informaticae, 2007)

Bayesian inference for latent variable models. - Ulrich Paquet (2007)

Improving on Expectation Propagation. - Manfred Opper; Ulrich Paquet; Ole Winther (NIPS, 2008)

Convexity and Bayesian constrained local models. - Ulrich Paquet (CVPR, 2009)

Perturbation Corrections in Approximate Inference: Mixture Modelling Applications. - Ulrich Paquet; Ole Winther; Manfred Opper (J. Mach. Learn. Res., 2009)

Transparent user models for personalization. - Khalid El-Arini; Ulrich Paquet; Ralf Herbrich; Jurgen Van Gael; Blaise Agüera y Arcas (KDD, 2012)

The Xbox recommender system. - Noam Koenigstein; Nir Nice; Ulrich Paquet; Nir Schleyen (RecSys, 2012)

Collaborative learning of preference rankings. - Tim Salimans; Ulrich Paquet; Thore Graepel (RecSys, 2012)

A hierarchical model for ordinal matrix factorization. - Ulrich Paquet; Blaise Thomson; Ole Winther (Stat. Comput., 2012)

Xbox movies recommendations: variational bayes matrix factorization with embedded feature selection. - Noam Koenigstein; Ulrich Paquet (RecSys, 2013)

One-class collaborative filtering with random graphs. - Ulrich Paquet; Noam Koenigstein (WWW, 2013)

One-class Collaborative Filtering with Random Graphs: Annotated Version. - Ulrich Paquet; Noam Koenigstein (CoRR, 2013)

Perturbative corrections for approximate inference in Gaussian latent variable models. - Manfred Opper; Ulrich Paquet; Ole Winther (J. Mach. Learn. Res., 2013)

Speeding up the Xbox recommender system using a euclidean transformation for inner-product spaces. - Yoram Bachrach; Yehuda Finkelstein; Ran Gilad-Bachrach; Liran Katzir 001; Noam Koenigstein; Nir Nice; Ulrich Paquet (RecSys, 2014)

A large-scale exploration of group viewing patterns. - Allison June-Barlow Chaney; Mike Gartrell; Jake M. Hofman; John Guiver; Noam Koenigstein; Pushmeet Kohli; Ulrich Paquet (TVX, 2014)

Indexable Probabilistic Matrix Factorization for Maximum Inner Product Search. - Marco Fraccaro; Ulrich Paquet; Ole Winther (AAAI, 2016)

Collective Noise Contrastive Estimation for Policy Transfer Learning. - Weinan Zhang 001; Ulrich Paquet; Katja Hofmann (AAAI, 2016)

Sequential Neural Models with Stochastic Layers. - Marco Fraccaro; Søren Kaae Sønderby; Ulrich Paquet; Ole Winther (NIPS, 2016)

Bayesian Low-Rank Determinantal Point Processes. - Mike Gartrell; Ulrich Paquet; Noam Koenigstein (RecSys, 2016)

Beyond Collaborative Filtering: The List Recommendation Problem. - Oren Sar Shalom; Noam Koenigstein; Ulrich Paquet; Hastagiri P. Vanchinathan (WWW, 2016)

Low-Rank Factorization of Determinantal Point Processes for Recommendation. - Mike Gartrell; Ulrich Paquet; Noam Koenigstein (CoRR, 2016)

The Bayesian Low-Rank Determinantal Point Process Mixture Model. - Mike Gartrell; Ulrich Paquet; Noam Koenigstein (CoRR, 2016)

Low-Rank Factorization of Determinantal Point Processes. - Mike Gartrell; Ulrich Paquet; Noam Koenigstein (AAAI, 2017)

Knowing What to Ask: A Bayesian Active Learning Approach to the Surveying Problem. - Yoad Lewenberg; Yoram Bachrach; Ulrich Paquet; Jeffrey S. Rosenschein (AAAI, 2017)

A Disentangled Recognition and Nonlinear Dynamics Model for Unsupervised Learning. - Marco Fraccaro; Simon Kamronn; Ulrich Paquet; Ole Winther (NIPS, 2017)

Groove Radio: A Bayesian Hierarchical Model for Personalized Playlist Generation. - Shay Ben-Elazar; Gal Lavee; Noam Koenigstein; Oren Barkan; Hilik Berezin; Ulrich Paquet; Tal Zaccai (WSDM, 2017)

Recurrent Relational Networks for Complex Relational Reasoning. - Rasmus Berg Palm; Ulrich Paquet; Ole Winther (CoRR, 2017)

Recurrent Relational Networks. - Rasmus Berg Palm; Ulrich Paquet; Ole Winther (NeurIPS, 2018)

An Efficient Implementation of Riemannian Manifold Hamiltonian Monte Carlo for Gaussian Process Models. - Ulrich Paquet; Marco Fraccaro (CoRR, 2018)

A Factorial Mixture Prior for Compositional Deep Generative Models. - Ulrich Paquet; Sumedh K. Ghaisas; Olivier Tieleman (CoRR, 2018)

Unsupervised Separation of Dynamics from Pixels. - Silvia Chiappa; Ulrich Paquet (CoRR, 2019)

Assessing Game Balance with AlphaZero: Exploring Alternative Rule Sets in Chess. - Nenad Tomasev; Ulrich Paquet; Demis Hassabis; Vladimir Kramnik (CoRR, 2020)

Acquisition of Chess Knowledge in AlphaZero. - Thomas McGrath; Andrei Kapishnikov; Nenad Tomasev; Adam Pearce; Demis Hassabis; Been Kim; Ulrich Paquet; Vladimir Kramnik (CoRR, 2021)

Role of Human-AI Interaction in Selective Prediction. - Elizabeth Bondi; Raphael Koster; Hannah Sheahan; Martin J. Chadwick; Yoram Bachrach; A. Taylan Cemgil; Ulrich Paquet; Krishnamurthy Dvijotham (AAAI, 2022)

Reimagining chess with AlphaZero. - Nenad Tomasev; Ulrich Paquet; Demis Hassabis; Vladimir Kramnik (Commun. ACM, 2022)

Bridging the Human-AI Knowledge Gap: Concept Discovery and Transfer in AlphaZero. - Lisa Schut; Nenad Tomasev; Tom McGrath; Demis Hassabis; Ulrich Paquet; Been Kim (CoRR, 2023)

Correlating Variational Autoencoders Natively For Multi-View Imputation. - Ella S. C. Orme; Marina Evangelou; Ulrich Paquet (UniReps, 2025)

Artificial intelligence for modelling infectious disease epidemics. - Moritz U. G. Kraemer; Joseph L.-H. Tsui; Serina Chang; Spyros Lytras; Mark P. Khurana; Samantha Vanderslott; Sumali Bajaj; Neil Scheidwasser; Jacob Liam Curran-Sebastian; Elizaveta Semenova; Mengyan Zhang; H. Juliette T. Unwin; et al. (Nat., 2025)