Research output per year
Research output per year
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Dive into the research topics where Nathan Kirk is active. These topic labels come from the works of this person. Together they form a unique fingerprint.
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Collaborations and top research areas from the last five years
Recent external collaboration on country/territory level. Dive into details by clicking on the dots or
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High-dimensional quasi-Monte Carlo via combinatorial discrepancy
Chen, J., Jiang, H. & Kirk, N., 1 Oct 2026, In: Journal of Complexity. 96, 23 p., 102053.Research output: Contribution to journal › Article › peer-review
Open AccessFile -
Neural low-discrepancy sequences
Huffel, M. E. V., Kirk, N., Chahine, M., Rus, D. & Rusch, T. K., 4 Oct 2025, arXiv, 18 p.Research output: Working paper › Preprint
Open Access -
Quasi-Monte Carlo methods: what, why, and how?
Hickernell, F. J., Kirk, N. & Sorokin, A. G., 5 Feb 2025, arXiv, 34 p.Research output: Working paper › Preprint
Open Access -
Message-passing Monte Carlo: generating low-discrepancy point sets via graph neural networks
Rusch, T. K., Kirk, N., Bronstein, M. M., Lemieux, C. & Rus, D., 1 Oct 2024, In: Proceedings of the National Academy of Sciences. 121, 40, 7 p., e2409913121.Research output: Contribution to journal › Article › peer-review
Open AccessFile
Datasets
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Message-passing Monte Carlo: generating low-discrepancy point sets via graph neural networks (
Kirk, N. (Creator), GitHub, 2026
https://github.com/tk-rusch/MPMC
Dataset: Software
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High-dimensional Quasi-Monte Carlo via combinatorial discrepancy (code)
Kirk, N. (Creator), GitHub, 2026
https://github.com/nmkirk/QMC_SubgTrans/
Dataset: Software