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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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Sequence Alignment with Dirichlet Process Mixtures


Nov 26, 2018
Ieva Kazlauskaite, Ivan Ustyuzhaninov, Carl Henrik Ek, Neill D. F. Campbell

* 6 pages, 3 figures, "All Of Bayesian Nonparametrics" Workshop at the 32nd Annual Conference on Neural Information Processing Systems ([email protected]

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Multimodal Deep Gaussian Processes


Oct 16, 2018
Markus Kaiser, Clemens Otte, Thomas Runkler, Carl Henrik Ek


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DP-GP-LVM: A Bayesian Non-Parametric Model for Learning Multivariate Dependency Structures


Jul 12, 2018
Andrew R. Lawrence, Carl Henrik Ek, Neill D. F. Campbell


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Gaussian Process Latent Variable Alignment Learning


Jul 05, 2018
Ieva Kazlauskaite, Carl Henrik Ek, Neill D. F. Campbell

* 13 pages, 10 figures 

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Bayesian Alignments of Warped Multi-Output Gaussian Processes


May 23, 2018
Markus Kaiser, Clemens Otte, Thomas Runkler, Carl Henrik Ek


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Model Inference with Stein Density Ratio Estimation


May 18, 2018
Song Liu, Wittawat Jitkrittum, Carl Henrik Ek


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Active Exploration Using Gaussian Random Fields and Gaussian Process Implicit Surfaces


Feb 13, 2018
Sergio Caccamo, Yasemin Bekiroglu, Carl Henrik Ek, Danica Kragic

* 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) 
* 8 pages, 6 figures, external contents (https://youtu.be/0-UlFRQT0JI

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Nonparametric Inference for Auto-Encoding Variational Bayes


Dec 18, 2017
Erik Bodin, Iman Malik, Carl Henrik Ek, Neill D. F. Campbell

* Presented at NIPS 2017 Workshop on Advances in Approximate Bayesian Inference 

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Latent Gaussian Process Regression


Sep 16, 2017
Erik Bodin, Neill D. F. Campbell, Carl Henrik Ek


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Neural Translation of Musical Style


Aug 11, 2017
Iman Malik, Carl Henrik Ek


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Manifold Alignment Determination: finding correspondences across different data views


Jan 12, 2017
Andreas Damianou, Neil D. Lawrence, Carl Henrik Ek

* NIPS workshop on Multi-Modal Machine Learning, 2015 

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Diagnostic Prediction Using Discomfort Drawings with IBTM


Sep 13, 2016
Cheng Zhang, Hedvig Kjellstrom, Carl Henrik Ek, Bo C. Bertilson

* Presented at 2016 Machine Learning and Healthcare Conference (MLHC 2016), Los Angeles, CA 

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Inter-Battery Topic Representation Learning


Jul 28, 2016
Cheng Zhang, Hedvig Kjellstrom, Carl Henrik Ek

* ECCV 2016 

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Unsupervised Learning with Imbalanced Data via Structure Consolidation Latent Variable Model


Jun 30, 2016
Fariba Yousefi, Zhenwen Dai, Carl Henrik Ek, Neil Lawrence

* ICLR 2016 Workshop 

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Multi-view Learning as a Nonparametric Nonlinear Inter-Battery Factor Analysis


Apr 17, 2016
Andreas Damianou, Neil D. Lawrence, Carl Henrik Ek

* 49 pages including appendix 

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On a Family of Decomposable Kernels on Sequences


Jan 26, 2015
Andrea Baisero, Florian T. Pokorny, Carl Henrik Ek


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Persistent Evidence of Local Image Properties in Generic ConvNets


Nov 24, 2014
Ali Sharif Razavian, Hossein Azizpour, Atsuto Maki, Josephine Sullivan, Carl Henrik Ek, Stefan Carlsson


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Factorized Topic Models


Apr 23, 2013
Cheng Zhang, Carl Henrik Ek, Andreas Damianou, Hedvig Kjellstrom

* ICLR 2013 

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