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2020 – today
- 2024
[i4]Daniel MacKinlay, Russell Tsuchida, Daniel Edward Pagendam, Petra Kuhnert:
Gaussian Ensemble Belief Propagation for Efficient Inference in High-Dimensional Systems. CoRR abs/2402.08193 (2024)- 2022
- [c3]Makoto Takamoto, Timothy Praditia, Raphael Leiteritz, Daniel MacKinlay, Francesco Alesiani, Dirk Pflüger, Mathias Niepert:
PDEBench: An Extensive Benchmark for Scientific Machine Learning. NeurIPS 2022 - [i3]Makoto Takamoto, Timothy Praditia, Raphael Leiteritz, Daniel MacKinlay, Francesco Alesiani, Dirk Pflüger, Mathias Niepert
:
PDEBENCH: An Extensive Benchmark for Scientific Machine Learning. CoRR abs/2210.07182 (2022) - [i2]Joel Janek Dabrowski, Daniel Edward Pagendam, James Hilton, Conrad Sanderson, Daniel MacKinlay, Carolyn Huston, Andrew Bolt, Petra Kuhnert:
Bayesian Physics Informed Neural Networks for Data Assimilation and Spatio-Temporal Modelling of Wildfires. CoRR abs/2212.00970 (2022) - 2020
- [j2]Nadhir Ben Rached, Daniel MacKinlay, Zdravko I. Botev, Raúl Tempone, Mohamed-Slim Alouini:
A Universal Splitting Estimator for the Performance Evaluation of Wireless Communications Systems. IEEE Trans. Wirel. Commun. 19(7): 4353-4362 (2020)
2010 – 2019
- 2019
- [j1]Zdravko I. Botev, Robert Salomone, Daniel MacKinlay:
Fast and accurate computation of the distribution of sums of dependent log-normals. Ann. Oper. Res. 280(1-2): 19-46 (2019) - [c2]Daniel MacKinlay, Zdravko I. Botev:
Mosaic Style Transfer Using Sparse Autocorrelograms. ISMIR 2019: 886-893 - [i1]Nadhir Ben Rached, Daniel MacKinlay, Zdravko I. Botev, Raúl Tempone, Mohamed-Slim Alouini:
A Universal Splitting Estimator for the Performance Evaluation of Wireless Communications Systems. CoRR abs/1908.10616 (2019) - 2017
- [c1]Zdravko I. Botev, Daniel MacKinlay, Yi-Lung Chen:
Logarithmically efficient estimation of the tail of the multivariate normal distribution. WSC 2017: 1903-1913
Coauthor Index
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