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Marginalising over Stationary Kernels with Bayesian Quadrature


Jun 14, 2021
Saad Hamid, Sebastian Schulze, Michael A. Osborne, Stephen J. Roberts


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Same State, Different Task: Continual Reinforcement Learning without Interference


Jun 05, 2021
Samuel Kessler, Jack Parker-Holder, Philip Ball, Stefan Zohren, Stephen J. Roberts

* 20 pages, 12 figures 

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OffCon$^3$: What is state of the art anyway?


Jan 27, 2021
Philip J. Ball, Stephen J. Roberts


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The Effect of Prior Lipschitz Continuity on the Adversarial Robustness of Bayesian Neural Networks


Jan 07, 2021
Arno Blaas, Stephen J. Roberts

* 4 pages, 2 tables, AAAI 2021 Workshop Towards Robust, Secure and Efficient Machine Learning 

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Introducing an Explicit Symplectic Integration Scheme for Riemannian Manifold Hamiltonian Monte Carlo


Oct 14, 2019
Adam D. Cobb, Atılım Güneş Baydin, Andrew Markham, Stephen J. Roberts


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Adaptive Configuration Oracle for Online Portfolio Selection Methods


Aug 22, 2019
Favour M. Nyikosa, Michael A. Osborne, Stephen J. Roberts


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Bayesian Heatmaps: Probabilistic Classification with Multiple Unreliable Information Sources


Apr 05, 2019
Edwin Simpson, Steven Reece, Stephen J. Roberts

* Joint European Conference on Machine Learning and Knowledge Discovery in Databases (2017), pp. 109-125, Springer, Cham 

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Asynchronous Batch Bayesian Optimisation with Improved Local Penalisation


Jan 30, 2019
Ahsan S. Alvi, Binxin Ru, Jan Calliess, Stephen J. Roberts, Michael A. Osborne

* formatting edits 

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Automated bird sound recognition in realistic settings


Sep 04, 2018
Timos Papadopoulos, Stephen J. Roberts, Katherine J. Willis


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Optimization, fast and slow: optimally switching between local and Bayesian optimization


May 22, 2018
Mark McLeod, Michael A. Osborne, Stephen J. Roberts


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Practical Bayesian Optimization for Variable Cost Objectives


May 15, 2018
Mark McLeod, Michael A. Osborne, Stephen J. Roberts

* 8 pages, 7 figures 

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Loss-Calibrated Approximate Inference in Bayesian Neural Networks


May 10, 2018
Adam D. Cobb, Stephen J. Roberts, Yarin Gal

* 12 pages, 12 figures 

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Quantum algorithms for training Gaussian Processes


Mar 28, 2018
Zhikuan Zhao, Jack K. Fitzsimons, Michael A. Osborne, Stephen J. Roberts, Joseph F. Fitzsimons

* 5 pages. Comments welcome 

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Bayesian Optimization for Dynamic Problems


Mar 09, 2018
Favour M. Nyikosa, Michael A. Osborne, Stephen J. Roberts

* 10 pages, 4 figures 

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Identifying Sources and Sinks in the Presence of Multiple Agents with Gaussian Process Vector Calculus


Feb 22, 2018
Adam D. Cobb, Richard Everett, Andrew Markham, Stephen J. Roberts

* 9 pages, 5 figures, conference submission, University of Oxford 

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Inferring agent objectives at different scales of a complex adaptive system


Dec 04, 2017
Dieter Hendricks, Adam Cobb, Richard Everett, Jonathan Downing, Stephen J. Roberts

* 6 pages, 3 figures, NIPS 2017 Workshop on Learning in the Presence of Strategic Behaviour (MLStrat) 

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Learning from lions: inferring the utility of agents from their trajectories


Sep 07, 2017
Adam D. Cobb, Andrew Markham, Stephen J. Roberts

* 9 pages, 4 figures 

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A Novel Approach to Forecasting Financial Volatility with Gaussian Process Envelopes


May 02, 2017
Syed Ali Asad Rizvi, Stephen J. Roberts, Michael A. Osborne, Favour Nyikosa

* 16 pages, 8 figures, 6 tables 

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Optimal client recommendation for market makers in illiquid financial products


Apr 27, 2017
Dieter Hendricks, Stephen J. Roberts

* 12 pages, 3 figures, 1 table 

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Distribution of Gaussian Process Arc Lengths


Mar 23, 2017
Justin D. Bewsher, Alessandra Tosi, Michael A. Osborne, Stephen J. Roberts

* 10 pages, 4 figures, Accepted to The 20th International Conference on Artificial Intelligence and Statistics (AISTATS) 

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A Sparse Gaussian Process Framework for Photometric Redshift Estimation


Oct 19, 2015
Ibrahim A. Almosallam, Sam N. Lindsay, Matt J. Jarvis, Stephen J. Roberts


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p-Markov Gaussian Processes for Scalable and Expressive Online Bayesian Nonparametric Time Series Forecasting


Oct 09, 2015
Yves-Laurent Kom Samo, Stephen J. Roberts


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A Variational Bayesian State-Space Approach to Online Passive-Aggressive Regression


Sep 08, 2015
Arnold Salas, Stephen J. Roberts, Michael A. Osborne


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Variational Inference for Gaussian Process Modulated Poisson Processes


Jul 27, 2015
Chris Lloyd, Tom Gunter, Michael A. Osborne, Stephen J. Roberts

* in ICML 2015 

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Sampling for Inference in Probabilistic Models with Fast Bayesian Quadrature


Nov 03, 2014
Tom Gunter, Michael A. Osborne, Roman Garnett, Philipp Hennig, Stephen J. Roberts

* Advances in Neural Information Processing Systems (NIPS) 2014 

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Efficient Bayesian Nonparametric Modelling of Structured Point Processes


Jul 25, 2014
Tom Gunter, Chris Lloyd, Michael A. Osborne, Stephen J. Roberts

* Proceedings of Uncertainty in Artificial Intelligence (UAI) 2014 
* Presented at UAI 2014. Bibtex: @inproceedings{structcoxpp14_UAI, Author = {Tom Gunter and Chris Lloyd and Michael A. Osborne and Stephen J. Roberts}, Title = {Efficient Bayesian Nonparametric Modelling of Structured Point Processes}, Booktitle = {Uncertainty in Artificial Intelligence (UAI)}, Year = {2014}} 

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Stochastic processes and feedback-linearisation for online identification and Bayesian adaptive control of fully-actuated mechanical systems


Apr 01, 2014
Jan-Peter Calliess, Antonis Papachristodoulou, Stephen J. Roberts


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Bayesian one-mode projection for dynamic bipartite graphs


Dec 12, 2012
Ioannis Psorakis, Iead Rezek, Zach Frankel, Stephen J. Roberts

* 11 pages, 5 figures 

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