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Dive into the research topics where Ari Pakman is active. These topic labels come from the works of this person. Together they form a unique fingerprint.
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  • A BAYESIAN NONPARAMETRIC APPROACH TO SUPER-RESOLUTION SINGLE-MOLECULE LOCALIZATION

    Gabitto, M. I., Marie-Nelly, H., Pakman, A., Pataki, A., Darzacq, X. & Jordan, M. I., 1 Dec 2021, In: Annals of Applied Statistics. 15, 4, p. 1742-1766 25 p.

    Research output: Contribution to journalArticlepeer-review

    Open Access
  • Estimating the Unique Information of Continuous Variables

    Pakman, A., Nejatbakhsh, A., Gilboa, D., Makkeh, A., Mazzucato, L., Wibral, M. & Schneidman, E., 1 Jan 2021, Advances in Neural Information Processing Systems 34 - 35th Conference on Neural Information Processing Systems, NeurIPS 2021. Ranzato, MA., Beygelzimer, A., Dauphin, Y., Liang, P. S. & Wortman Vaughan, J. (eds.). p. 20295-20307 13 p. (Advances in Neural Information Processing Systems; vol. 24).

    Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

  • Neural clustering processes

    Pakman, A., Wang, Y., Mitelut, C., Lee, J. H. & Paninski, L., 1 Jan 2020, 37th International Conference on Machine Learning, ICML 2020. Daume, H. & Singh, A. (eds.). p. 7411-7421 11 p. (37th International Conference on Machine Learning, ICML 2020; vol. PartF168147-10).

    Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

  • Neural Permutation Processes

    Pakman, A., Wang, Y. & Paninski, L., 1 Jan 2019, In: Proceedings of Machine Learning Research. 118

    Research output: Contribution to journalConference articlepeer-review

  • Stochastic bouncy particle sampler

    Pakman, A., Gilboa, D., Carlson, D. & Paninski, L., 1 Jan 2017, 34th International Conference on Machine Learning, ICML 2017. p. 4186-4208 23 p. (34th International Conference on Machine Learning, ICML 2017; vol. 6).

    Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review