Publications & Preprints

M. Etienne, N. Kirk, M. Chahine, D. Rus, T. K. Rusch. Neural Low-Discrepancy Sequences. Preprint, arXiv/2510.03745 (2025)

J. Chen, H. Jiang, N. Kirk. High-Dimensional Quasi-Monte Carlo via Combinatorial Discrepancy. Preprint, arXiv/2508.18426 (2025)

F. Clément, N. Kirk, A. B. Owen, T. K. Rusch. On the optimization of discrepancy measures. Preprint, arXiv/2508.04926 (2025)

N. Kirk, I. Gvozdanović, S. Petrović. Multilevel Sampling in Algebraic Statistics. Preprint, arXiv/2505.04062 (2025)

N. Kirk, T. K. Rusch, Z. Zech, D. Rus. Low Stein discrepancy via Message-Passing Monte Carlo. Preprint, arXiv/2503.21103 (2025)

F. J. Hickernell, N. Kirk, A. G. Sorokin. Quasi-Monte Carlo Methods: What, Why and How?  Preprint, arXiv/2502.03644 (2025)

A. Emmett-Iwanwi, N. Kirk. Enhancing neural autoregressive distribution estimators for image reconstruction. Preprint, arXiv/2506.05391 (2025)

T. K. Rusch, N. Kirk, M. Bronstein, C. Lemieux, D. Rus. Message-Passing Monte Carlo: Generating low-discrepancy point sets via graph neural networks. Proc. Natl. Acad. Sci. U.S.A. (PNAS), 121 (40), e2409913121 (2024)

N. Kirk, C. Lemieux. An Improved Halton Sequence for Implementation in Quasi-Monte Carlo Methods. Proceedings of the 2024 Winter Simulation Conference. IEEE Press, 431-442 (2025)

N. Kirk, C. Lemieux, J. Wiart. Golden ratio nets and sequences. Funct. Approx. Comment. Math. 73 (1), 97-141 (2025)

F. Clément, N. Kirk, F. Pausinger. Partitions for Stratified Sampling. Monte Carlo Methods Appl., 30 (2), 163-181 (2024)

N. Kirk, F. Pausinger. On the Expected L2-discrepancy of Jittered Sampling. Unif. Dist. Theory, 18 (1), 65-82 (2023)

N. Kirk. On Proinov's Lower Bound for the Diaphony. Unif. Dist. Theory, 15 (2), 39-72 (2020)