Sustainability and Machine Learning Group
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The Graph Cut Kernel for Ranked Data
Many algorithms for ranked data become computationally intractable as the number of objects grows due to the complex geometric …
Michelangelo Conserva
,
Marc P. Deisenroth
,
K. S. Sesh Kumar
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Iterative State Estimation in Non-linear Dynamical Systems Using Approximate Expectation Propagation
Bayesian inference in non-linear dynamical systems seeks to find good posterior approximations of a latent state given a sequence of …
Sanket Kamthe
,
So Takao
,
Shakir Mohamed
,
Marc P. Deisenroth
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Cauchy-Schwarz Regularized Autoencoder
Recent work in unsupervised learning has focused on efficient inference and learning in latent variables models. Training these models …
Linh Tran
,
Maja Pantic
,
Marc P. Deisenroth
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Network topological determinants of pathogen spread
Marı́a Pérez-Ortiz
,
Petru Manescu
,
Fabio Caccioli
,
Delmiro Fernández-Reyes
,
Parashkev Nachev
,
John Shawe-Taylor
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Power to the Learner: Towards Human-Intuitive and Integrative Recommendations with Open Educational Resources
Sahan Bulathwela
,
Marı́a Pérez-Ortiz
,
Emine Yilmaz
,
John Shawe-Taylor
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Pathwise Conditioning of Gaussian Processes
As Gaussian processes are used to answer increasingly complex questions, analytic solutions become scarcer and scarcer. Monte Carlo …
James T. Wilson
,
Viacheslav Borovitskiy
,
Alexander Terenin
,
Peter Mostowsky
,
Marc P. Deisenroth
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GPflux: A Library for Deep Gaussian Processes
We introduce GPflux, a Python library for Bayesian deep learning with a strong emphasis on deep Gaussian processes (DGPs). Implementing …
Vincent Dutordoir
,
Hugh Salimbeni
,
Eric Hambro
,
John McLeod
,
Felix Leibfried
,
Artem Artemev
,
Mark Van Der Wilk
,
James Hensman
,
Marc P. Deisenroth
,
St John
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Simultaneous Tactile Exploration and Grasp Refinement for Unknown Objects
Christiana De Farias
,
Naresh Marturi
,
Rustam Stolkin
,
Yasemin Bekiroğlu
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Learning PAC-Bayes Priors for Probabilistic Neural Networks
Marı́a Pérez-Ortiz
,
Omar Rivasplata
,
Benjamin Guedj
,
Matthew Gleeson
,
Jingyu Zhang
,
John Shawe-Taylor
,
Miroslaw Bober
,
Josef Kittler
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Seasonal Arctic sea ice forecasting with probabilistic deep learning
Tom R Andersson
,
J Scott Hosking
,
Maria Pérez-Ortiz
,
Brooks Paige
,
Andrew Elliott
,
Chris Russell
,
Stephen Law
,
Daniel C Jones
,
Jeremy Wilkinson
,
Tony Phillips
,
Others
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