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Cioica-Licht, P. A., Cox, S. G., & Veraar, M. C. (2023). Stochastic integration in quasi-Banach spaces. Studia Mathematica, 269, 1-64. https://doi.org/10.48550/arXiv.1804.08947, https://doi.org/10.4064/SM180424-31-10 -
Ellis-Monaghan, J., & Jonoska, N. (2023). From Molecules to Mathematics. In N. Jonoska, & E. Winfree (Eds.), Visions of DNA Nanotechnology at 40 for the Next 40: A Tribute to Nadrian C. Seeman (pp. 189-206). (Natural Computing Series). Springer. https://doi.org/10.1007/978-981-19-9891-1_11
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Chan, K. M. D., & Mandjes, M. R. H. (2023). A Versatile Stochastic Dissemination Model. Methodology and Computing in Applied Probability, 25(3), Article 69. https://doi.org/10.1007/s11009-023-10041-2
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Kopparty, S., Moshkovitz, G., & Zuiddam, J. (2023). Geometric Rank of Tensors and Subrank of Matrix Multiplication. Discrete Analysis, 2023, Article 1. https://doi.org/10.48550/arXiv.2002.09472
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Stevenson, R., & Storn, J. (2023). Interpolation operators for parabolic problems. Numerische Mathematik, 155(1-2), 211-238. https://doi.org/10.1007/s00211-023-01373-9
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Siteur, K., Liu, Q.-X., Rottschäfer, V., van der Heide, T., Rietkerk, M., Doelman, A., Boström, C., & van de Koppel, J. (2023). Phase-separation physics underlies new theory for the resilience of patchy ecosystems. Proceedings of the National Academy of Sciences, 120(2), Article e2202683120. https://doi.org/10.1073/pnas.2202683120
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Hadiji, H., Sachs, S., van Even, T., & Koolen, W. (2023). Towards Characterizing the First-order Query Complexity of Learning (Approximate) Nash Equilibria in Zero-sum Matrix Games. In A. Oh, T. Naumann, A. Globerson, K. Saenko, M. Hardt, & S. Levine (Eds.), 37th Conference on Neural Information Processing Systems (NeurIPS 2023): 10-16 December 2023, New Orleans, Louisana, USA (pp. 13356-13373). (Advances in Neural Information Processing Systems; Vol. 36). Neural Information Processing Systems Foundation. https://papers.nips.cc/paper_files/paper/2023/hash/2af57f909a99113db071672da236a5f2-Abstract-Conference.html
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Cléry, F., & van der Geer, G. (2023). Generating Picard modular forms by means of invariant theory. Pure and Applied Mathematics Quarterly, 19(1), 95-147. https://doi.org/10.48550/arXiv.2110.00849, https://doi.org/10.4310/PAMQ.2023.v19.n1.a6
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Ghosh, M., Kuiper, A., Mahes, R., & Maragno, D. (2023). Learn global and optimize local: A data-driven methodology for last-mile routing. Computers and Operations Research, 159, Article 106312. https://doi.org/10.1016/j.cor.2023.106312
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de Boer, D., Buys, P., & Regts, G. (2023). Uniqueness of the Gibbs measure for the 4-state anti-ferromagnetic Potts model on the regular tree. Combinatorics Probability and Computing, 32(1), 158-182. https://doi.org/10.1017/S0963548322000207
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