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Daniel Giles
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2020 – today
- 2024
- [i5]Oscar Key, So Takao, Daniel Giles, Marc Peter Deisenroth:
Scalable Data Assimilation with Message Passing. CoRR abs/2404.12968 (2024) - [i4]Daniel Giles, James Briant, Cyril Morcrette, Serge Guillas:
Embedding machine-learnt sub-grid variability improves climate model biases. CoRR abs/2406.09551 (2024) - [i3]Vignesh Gopakumar, Joel Oskarrson, Ander Gray, Lorenzo Zanisi, Stanislas Pamela, Daniel Giles, Matt Kusner, Marc Peter Deisenroth:
Valid Error Bars for Neural Weather Models using Conformal Prediction. CoRR abs/2406.14483 (2024) - [i2]Vignesh Gopakumar, Ander Gray, Joel Oskarsson, Lorenzo Zanisi, Stanislas Pamela, Daniel Giles, Matt Kusner, Marc Peter Deisenroth:
Uncertainty Quantification of Pre-Trained and Fine-Tuned Surrogate Models using Conformal Prediction. CoRR abs/2408.09881 (2024) - 2023
- [c1]Kaiyu Li, Daniel Giles, Toni Karvonen, Serge Guillas, François-Xavier Briol:
Multilevel Bayesian Quadrature. AISTATS 2023: 1845-1868 - 2020
- [i1]Daniel Giles
, Eugene Kashdan, Dimitra M. Salmanidou, Serge Guillas, Frédéric Dias:
Performance analysis of Volna-OP2 - massively parallel code for tsunami modelling. CoRR abs/2002.04889 (2020)
2010 – 2019
- 2017
- [j2]Nguyen Mau Nam
Minimizing Differences of Convex Functions with Applications to Facility Location and Clustering. J. Optim. Theory Appl. 173(1): 255-278 (2017) - 2016
- [j1]Nguyen Thai An, Daniel Giles, Nguyen Mau Nam, R. Blake Rector:
The Log-Exponential Smoothing Technique and Nesterov's Accelerated Gradient Method for Generalized Sylvester Problems. J. Optim. Theory Appl. 168(2): 559-583 (2016)
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last updated on 2024-09-26 00:57 CEST by the dblp team
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