Logarithmically efficient estimation of the tail of the multivariate normal distribution. - Zdravko I. Botev; Daniel MacKinlay; Yi-Lung Chen (WSC, 2017)

Mosaic Style Transfer Using Sparse Autocorrelograms. - Daniel MacKinlay; Zdravko I. Botev (ISMIR, 2019)

Fast and accurate computation of the distribution of sums of dependent log-normals. - Zdravko I. Botev; Robert Salomone; Daniel MacKinlay (Ann. Oper. Res., 2019)

A Universal Splitting Estimator for the Performance Evaluation of Wireless Communications Systems. - Nadhir Ben Rached; Daniel MacKinlay; Zdravko I. Botev; Raúl Tempone; Mohamed-Slim Alouini (IEEE Trans. Wirel. Commun., 2020)

PDEBench: An Extensive Benchmark for Scientific Machine Learning. - Makoto Takamoto; Timothy Praditia; Raphael Leiteritz; Daniel MacKinlay; Francesco Alesiani; Dirk Pflüger; Mathias Niepert (NeurIPS, 2022)

Bayesian Physics Informed Neural Networks for Data Assimilation and Spatio-Temporal Modelling of Wildfires. - Joel Janek Dabrowski; Daniel Edward Pagendam; James Hilton 001; Conrad Sanderson; Daniel MacKinlay; Carolyn Huston; Andrew Bolt; Petra Kuhnert (CoRR, 2022)

PDEBench Pretrained Models. - Makoto Takamoto; Timothy Praditia; Raphael Leiteritz; Daniel MacKinlay; Francesco Alesiani; Dirk Pflüger; Mathias Niepert (DaRUS, 2022)

PDEBench Datasets. - Makoto Takamoto; Timothy Praditia; Raphael Leiteritz; Daniel MacKinlay; Francesco Alesiani; Dirk Pflüger; Mathias Niepert (DaRUS, 2022)

PDEBench Datasets. - Makoto Takamoto; Timothy Praditia; Raphael Leiteritz; Daniel MacKinlay; Francesco Alesiani; Dirk Pflüger; Mathias Niepert (DaRUS, 2022)

PDEBench Datasets. - Makoto Takamoto; Timothy Praditia; Raphael Leiteritz; Daniel MacKinlay; Francesco Alesiani; Dirk Pflüger; Mathias Niepert (DaRUS, 2023)

PDEBench Datasets. - Makoto Takamoto; Timothy Praditia; Raphael Leiteritz; Daniel MacKinlay; Francesco Alesiani; Dirk Pflüger; Mathias Niepert (DaRUS, 2023)

PDEBench Datasets. - Makoto Takamoto; Timothy Praditia; Raphael Leiteritz; Daniel MacKinlay; Francesco Alesiani; Dirk Pflüger; Mathias Niepert (DaRUS, 2023)

PDEBench Datasets. - Makoto Takamoto; Timothy Praditia; Raphael Leiteritz; Daniel MacKinlay; Francesco Alesiani; Dirk Pflüger; Mathias Niepert (DaRUS, 2023)

PDEBench Pretrained Models. - Makoto Takamoto; Timothy Praditia; Raphael Leiteritz; Daniel MacKinlay; Francesco Alesiani; Dirk Pflüger; Mathias Niepert (DaRUS, 2023)

PDEBench Datasets. - Makoto Takamoto; Timothy Praditia; Raphael Leiteritz; Daniel MacKinlay; Francesco Alesiani; Dirk Pflüger; Mathias Niepert (DaRUS, 2023)

Gaussian Ensemble Belief Propagation for Efficient Inference in High-Dimensional Systems. - Daniel MacKinlay; Russell Tsuchida; Daniel Edward Pagendam; Petra Kuhnert (CoRR, 2024)

PDEBench Datasets. - Makoto Takamoto; Timothy Praditia; Raphael Leiteritz; Daniel MacKinlay; Francesco Alesiani; Dirk Pflüger; Mathias Niepert (DaRUS, 2024)

Gaussian Ensemble Belief Propagation for Efficient Inference in High-Dimensional, Black-box Systems. - Daniel MacKinlay; Russell Tsuchida; Daniel Edward Pagendam; Petra Kuhnert (ICLR, 2025)