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Deep learning for monthly Arctic sea ice concentration prediction

Tom Andersson, Fruzsina Agocs, Scott Hosking, Marı́a Pérez-Ortiz, Brooks Paige, Chris Russell, Andrew Elliott, Stephen Law, Jeremy Wilkinson, Yevgeny Askenov, others

Predicting Engagement in Video Lectures

Sahan Bulathwela, Marı́a Pérez-Ortiz, Aldo Lipani, Emine Yilmaz, John Shawe-Taylor

SUM'20: State-based User Modelling

Sahan Bulathwela, Marı́a Pérez-Ortiz, Rishabh Mehrotra, Davor Orlic, Colin de la Higuera, John Shawe-Taylor, Emine Yilmaz

Towards self-certified learning: Probabilistic neural networks trained by PAC-Bayes with Backprop

Marı́a Pérez-Ortiz, Omar Rivasplata, John Shawe-Taylor, Csaba Szepesvári

TrueLearn: A Family of Bayesian Algorithms to Match Lifelong Learners to Open Educational Resources

Sahan Bulathwela, Maria Perez-Ortiz, Emine Yilmaz, John Shawe-Taylor

What's in it for me? Augmenting Recommended Learning Resources with Navigable Annotations

Sahan Bulathwela, Stefan Kreitmayer, Marı́a Pérez-Ortiz

Disentangled Skill Embeddings for Reinforcement Learning

Janith C. Petangoda, Sergio Pascoal-Diaz, Vincent Adam, Peter Vrancx, Jordi Grau-Moya

High-Dimensional Bayesian Optimization Using Low-Dimensional Feature Spaces

Riccardo Moriconi, Marc P. Deisenroth, K. S. Sesh Kumar

On the Gromov-Wasserstein distance and Coupled Deep Generative Models

Samuel Cohen, Dino Sejdinovic

Variational Integrator Networks

Steindór Sæmundsson, Katja Hofmann, Marc Deisenroth