Constrained Bayesian optimization for automatic chemical design using variational autoencoders von Griffiths, Ryan-Rhys, Hernández-Lobato, José Miguel

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Data-driven discovery of molecular photoswitches with multioutput Gaussian processes von Griffiths, Ryan-Rhys, Greenfield, Jake L, Thawani, Aditya R, Jamasb, Arian R, Moss, Henry B, Bourached, Anthony, Jones, Penelope, McCorkindale, William, Aldrick, Alexander A, Fuchter, Matthew J, Lee, Alpha A

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Achieving robustness to aleatoric uncertainty with heteroscedastic Bayesian optimisation von Griffiths, Ryan-Rhys, A Aldrick, Alexander, Garcia-Ortegon, Miguel, Lalchand, Vidhi, Lee, Alpha A

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Generative model‐enhanced human motion prediction von Bourached, Anthony, Griffiths, Ryan‐Rhys, Gray, Robert, Jha, Ashwani, Nachev, Parashkev

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Analyzing global utilization and missed opportunities in debt-for-nature swaps with generative AI von Tkachenko, Nataliya, Frieder, Simon, Griffiths, Ryan-Rhys, Nedopil, Christoph

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Mapping Materials and Molecules von Cheng, Bingqing, Griffiths, Ryan-Rhys, Wengert, Simon, Kunkel, Christian, Stenczel, Tamas, Zhu, Bonan, Deringer, Volker L, Bernstein, Noam, Margraf, Johannes T, Reuter, Karsten, Csanyi, Gabor

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Modeling the Multiwavelength Variability of Mrk 335 Using Gaussian Processes von Griffiths, Ryan-Rhys, Jiang, Jiachen, Buisson, Douglas J. K., Wilkins, Dan, Gallo, Luigi C., Ingram, Adam, Lee, Alpha A., Grupe, Dirk, Kara, Erin, Parker, Michael L., Alston, William, Bourached, Anthony, Cann, George, Young, Andrew, Komossa, S.

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Bayesian optimisation for additive screening and yield improvements - beyond one-hot encoding von Rankovi, Bojana, Griffiths, Ryan-Rhys, Moss, Henry B, Schwaller, Philippe

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Applications of Gaussian Processes at Extreme Lengthscales: From Molecules to Black Holes von Griffiths, Ryan-Rhys

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On the voltage-controlled assembly of nanoparticle arrays at electrochemical solid/liquid interfaces von Zagar, Cristian, Griffiths, Ryan-Rhys, Podgornik, Rudolf, Kornyshev, Alexei A.

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Style transfer for improved visualization of underdrawings and ghost paintings: An application to a work by Vincent van Gogh von Bourached, Anthony, Cann, George H., Griffiths, Ryan-Rhys, Eriksson, Jesper, Stork, David G.

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Achieving Robustness to Aleatoric Uncertainty with Heteroscedastic Bayesian Optimisation von Ryan-Rhys Griffiths, Aldrick, Alexander A, Garcia-Ortegon, Miguel, Lalchand, Vidhi R, Lee, Alpha A

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Constrained Bayesian optimization for automatic chemical design using variational autoencoders† †Electronic supplementary information (ESI) available: Additional experimental resul... von Griffiths, Ryan-Rhys, Hernández-Lobato, José Miguel

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Modelling the Multiwavelength Variability of Mrk 335 using Gaussian Processes von Ryan-Rhys Griffiths, Jiang, Jiachen, Buisson, Douglas J K, Wilkins, Dan R, Gallo, Luigi C, Ingram, Adam, Lee, Alpha A, Grupe, Dirk, Kara, Erin, Parker, Michael L, Alston, William, Bourached, Anthony, Cann, George, Young, Andrew, Komossa, S

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HEBO: An Empirical Study of Assumptions in Bayesian Optimisation von Cowen-Rivers, Alexander I., Lyu, Wenlong, Tutunov, Rasul, Wang, Zhi, Grosnit, Antoine, Griffiths, Ryan Rhys, Maraval, Alexandre Max, Jianye, Hao, Wang, Jun, Peters, Jan, Bou-Ammar, Haitham

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HEBO: Pushing The Limits of Sample-Efficient Hyper-parameter Optimisation von Cowen-Rivers, Alexander I, Lyu, Wenlong, Tutunov, Rasul, Wang, Zhi, Grosnit, Antoine, Griffiths, Ryan Rhys, Maraval, Alexandre Max, Hao Jianye, Wang, Jun, Peters, Jan, Bou-Ammar, Haitham

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Applications of Gaussian Processes at Extreme Lengthscales: From Molecules to Black Holes von Griffiths, Ryan-Rhys

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Recovery of underdrawings and ghost-paintings via style transfer by deep convolutional neural networks: A digital tool for art scholars von Bourached, Anthony, Cann, George H., Griffths, Ryan-Rhys, Stork, David G.

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Computational identification of significant actors in paintings through symbols and attributes von Stork, David G., Bourached, Anthony, Cann, George H., Griffths, Ryan-Rhys

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Resolution enhancement in the recovery of underdrawings via style transfer by generative adversarial deep neural networks von Cann, George H., Bourached, Anthony, Griffths, Ryan-Rhys, Stork, David G.

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