Sustainability and Machine Learning Group
Sustainability and Machine Learning Group
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Plasma Surrogate Modelling using Fourier Neural Operators
Predicting plasma evolution within a Tokamak reactor is crucial to realizing the goal of sustainable fusion. Capabilities in …
Vignesh Gopakumar
,
Stanislas Pamela
,
Lorenzo Zanisi
,
Zongyi Li
,
Ander Gray
,
Daniel Brennand
,
Nitesh Bhatia
,
Gregory Stathopoulos
,
Matt Kusner
,
Marc P. Deisenroth
,
Anima Anandkumar
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Faster Training of Neural ODEs Using Gauß–Legendre Quadrature
Neural ODEs demonstrate strong performance in generative and time-series modelling. However, training them via the adjoint method is …
Alexander L. I. Norcliffe
,
Marc P. Deisenroth
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Video
Grasp Transfer based on Self-Aligning Implicit Representations of Local Surfaces
Objects we interact with and manipulate often share similar parts, e.g. handles, that allow us to transfer our actions flexibly due to …
Ahmet Tekden
,
Marc P. Deisenroth
,
Yasemin Bekiroğlu
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Boosting precision crop protection towards agriculture 5.0 via machine learning and emerging technologies: A contextual review
Gustavo A Mesı́as-Ruiz
,
Mar\á Pérez-Ortiz
,
José Dorado
,
Ana I de Castro
,
José M Peña
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TrueLearn: A Python Library for Personalised Informational Recommendations with (Implicit) Feedback
Yuxiang Qiu
,
Karim Djemili
,
Denis Elezi
,
Aaneel Shalman
,
Marı́a Pérez-Ortiz
,
Sahan Bulathwela
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Enhanced GPIS Learning Based on Local and Global Focus Areas
Implicit surface learning is one of the most widely used methods for 3D surface reconstruction from raw point cloud data. Current …
Zuka Murvanidze
,
Marc P. Deisenroth
,
Yasemin Bekiroğlu
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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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Reviews
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Blog
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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