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Aligned Multi-Task Gaussian Process


Oct 29, 2021
Olga Mikheeva, Ieva Kazlauskaite, Adam Hartshorne, Hedvig Kjellström, Carl Henrik Ek, Neill D. F. Campbell


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Deep Neural Networks as Point Estimates for Deep Gaussian Processes


May 10, 2021
Vincent Dutordoir, James Hensman, Mark van der Wilk, Carl Henrik Ek, Zoubin Ghahramani, Nicolas Durrande


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Black-box density function estimation using recursive partitioning


Oct 26, 2020
Erik Bodin, Zhenwen Dai, Neill D. F. Campbell, Carl Henrik Ek


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Bayesian nonparametric shared multi-sequence time series segmentation


Jan 27, 2020
Olga Mikheeva, Ieva Kazlauskaite, Hedvig Kjellström, Carl Henrik Ek


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Compositional uncertainty in deep Gaussian processes


Sep 17, 2019
Ivan Ustyuzhaninov, Ieva Kazlauskaite, Markus Kaiser, Erik Bodin, Neill D. F. Campbell, Carl Henrik Ek


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Interpretable Dynamics Models for Data-Efficient Reinforcement Learning


Jul 10, 2019
Markus Kaiser, Clemens Otte, Thomas Runkler, Carl Henrik Ek

* ESANN 2019 proceedings, European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning. Bruges (Belgium), 24-26 April 2019, i6doc.com publ., ISBN 978-287-587-065-0 

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Modulated Bayesian Optimization using Latent Gaussian Process Models


Jun 26, 2019
Erik Bodin, Markus Kaiser, Ieva Kazlauskaite, Neill D. F. Campbell, Carl Henrik Ek


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Monotonic Gaussian Process Flow


May 30, 2019
Ivan Ustyuzhaninov, Ieva Kazlauskaite, Carl Henrik Ek, Neill D. F. Campbell

* 14 pages 

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Invariant Feature Mappings for Generalizing Affordance Understanding Using Regularized Metric Learning


Jan 30, 2019
Martin Hjelm, Carl Henrik Ek, Renaud Detry, Danica Kragic


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Gaussian Process Deep Belief Networks: A Smooth Generative Model of Shape with Uncertainty Propagation


Dec 13, 2018
Alessandro Di Martino, Erik Bodin, Carl Henrik Ek, Neill D. F. Campbell


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