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Vector-valued Gaussian Processes on Riemannian Manifolds via Gauge Independent Projected Kernels


Nov 25, 2021
Michael Hutchinson, Alexander Terenin, Viacheslav Borovitskiy, So Takao, Yee Whye Teh, Marc Peter Deisenroth

* Advances in Neural Information Processing Systems, 2021 

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Vector-valued Gaussian Processes on Riemannian Manifolds via Gauge Equivariant Projected Kernels


Oct 28, 2021
Michael Hutchinson, Alexander Terenin, Viacheslav Borovitskiy, So Takao, Yee Whye Teh, Marc Peter Deisenroth

* Advances in Neural Information Processing Systems, 2021 

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Gaussian Process Sampling and Optimization with Approximate Upper and Lower Bounds


Oct 22, 2021
Vu Nguyen, Marc Peter Deisenroth, Michael A. Osborne

* 19 pages 

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Learning to Transfer: A Foliated Theory


Jul 22, 2021
Janith Petangoda, Marc Peter Deisenroth, Nicholas A. M. Monk


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Submodular Kernels for Efficient Rankings


May 26, 2021
Michelangelo Conserva, Marc Peter Deisenroth, K S Sesh Kumar


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Learning Contact Dynamics using Physically Structured Neural Networks


Feb 22, 2021
Andreas Hochlehnert, Alexander Terenin, Steindór Sæmundsson, Marc Peter Deisenroth

* Artificial Intelligence and Statistics, 2021 

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Sliced Multi-Marginal Optimal Transport


Feb 14, 2021
Samuel Cohen, K S Sesh Kumar, Marc Peter Deisenroth


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Healing Products of Gaussian Processes


Feb 14, 2021
Samuel Cohen, Rendani Mbuvha, Tshilidzi Marwala, Marc Peter Deisenroth

* ICML 2020 

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Cauchy-Schwarz Regularized Autoencoder


Feb 12, 2021
Linh Tran, Maja Pantic, Marc Peter Deisenroth


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Design of Dynamic Experiments for Black-Box Model Discrimination


Feb 07, 2021
Simon Olofsson, Eduardo S. Schultz, Adel Mhamdi, Alexander Mitsos, Marc Peter Deisenroth, Ruth Misener


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GENNI: Visualising the Geometry of Equivalences for Neural Network Identifiability


Nov 14, 2020
Daniel Lengyel, Janith Petangoda, Isak Falk, Kate Highnam, Michalis Lazarou, Arinbjörn Kolbeinsson, Marc Peter Deisenroth, Nicholas R. Jennings


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Pathwise Conditioning of Gaussian Processes


Nov 08, 2020
James T. Wilson, Viacheslav Borovitskiy, Alexander Terenin, Peter Mostowsky, Marc Peter Deisenroth


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Matern Gaussian Processes on Graphs


Oct 29, 2020
Viacheslav Borovitskiy, Iskander Azangulov, Alexander Terenin, Peter Mostowsky, Marc Peter Deisenroth, Nicolas Durrande


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A Foliated View of Transfer Learning


Aug 02, 2020
Janith Petangoda, Nick A. M. Monk, Marc Peter Deisenroth

* 14 pages, 6 figures 

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Probabilistic Active Meta-Learning


Jul 17, 2020
Jean Kaddour, Steindór Sæmundsson, Marc Peter Deisenroth


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Estimating Barycenters of Measures in High Dimensions


Jul 14, 2020
Samuel Cohen, Michael Arbel, Marc Peter Deisenroth

* In submission 

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Stochastic Differential Equations with Variational Wishart Diffusions


Jun 26, 2020
Martin Jørgensen, Marc Peter Deisenroth, Hugh Salimbeni

* ICML 2020 

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Aligning Time Series on Incomparable Spaces


Jun 22, 2020
Samuel Cohen, Giulia Luise, Alexander Terenin, Brandon Amos, Marc Peter Deisenroth


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Matern Gaussian processes on Riemannian manifolds


Jun 17, 2020
Viacheslav Borovitskiy, Alexander Terenin, Peter Mostowsky, Marc Peter Deisenroth


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Efficiently sampling functions from Gaussian process posteriors


Feb 21, 2020
James T. Wilson, Viacheslav Borovitskiy, Alexander Terenin, Peter Mostowsky, Marc Peter Deisenroth


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Variational Integrator Networks for Physically Meaningful Embeddings


Oct 21, 2019
Steindor Saemundsson, Alexander Terenin, Katja Hofmann, Marc Peter Deisenroth


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Deep Gaussian Processes with Importance-Weighted Variational Inference


May 14, 2019
Hugh Salimbeni, Vincent Dutordoir, James Hensman, Marc Peter Deisenroth

* Appearing ICML 2019 

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Differentially Private Empirical Risk Minimization with Sparsity-Inducing Norms


May 13, 2019
K S Sesh Kumar, Marc Peter Deisenroth


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Meta Reinforcement Learning with Latent Variable Gaussian Processes


Jul 07, 2018
Steindór Sæmundsson, Katja Hofmann, Marc Peter Deisenroth

* 11 pages, 7 figures 

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Design of Experiments for Model Discrimination Hybridising Analytical and Data-Driven Approaches


May 31, 2018
Simon Olofsson, Marc Peter Deisenroth, Ruth Misener


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Maximizing acquisition functions for Bayesian optimization


May 25, 2018
James T. Wilson, Frank Hutter, Marc Peter Deisenroth


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Data-Efficient Reinforcement Learning with Probabilistic Model Predictive Control


Feb 22, 2018
Sanket Kamthe, Marc Peter Deisenroth

* Accepted at AISTATS 2018, 

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The reparameterization trick for acquisition functions


Dec 01, 2017
James T. Wilson, Riccardo Moriconi, Frank Hutter, Marc Peter Deisenroth

* Accepted at the NIPS 2017 Workshop on Bayesian Optimization (BayesOpt 2017) 

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