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Collaborations and top research areas from the last five years
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Bayesian Circular Regression with von Mises Quasi-Processes
Cohen, Y., Navarro, A., Frellsen, J., Turner, R. E., Riemer, R. & Pakman, A., 1 Jan 2025, In: Proceedings of Machine Learning Research. 258, p. 1693-1701 9 p.Research output: Contribution to journal › Conference article › peer-review
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Clustering via Self-Supervised Diffusion
Uziel, R., Chelly, I., Freifeld, O. & Pakman, A., 1 Jan 2025, In: Proceedings of Machine Learning Research. 267, p. 60711-60726 16 p.Research output: Contribution to journal › Conference article › peer-review
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Consistent Amortized Clustering via Generative Flow Networks
Chelly, I., Uziel, R., Freifeld, O. & Pakman, A., 1 Jan 2025, In: Proceedings of Machine Learning Research. 258, p. 1729-1737 9 p.Research output: Contribution to journal › Conference article › peer-review
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Super-efficient exact Hamiltonian Monte Carlo for the von Mises distribution
Pakman, A., 1 Jan 2025, In: Applied Mathematics Letters. 159, 109284.Research output: Contribution to journal › Article › peer-review
2 Scopus citations -
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 journal › Article › peer-review
Open Access5 Scopus citations -
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, M., Beygelzimer, A., Dauphin, Y., Liang, P. S. & Wortman Vaughan, J. (eds.). Neural information processing systems foundation, p. 20295-20307 13 p. (Advances in Neural Information Processing Systems; vol. 24).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review
19 Scopus citations -
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.). International Machine Learning Society (IMLS), p. 7411-7421 11 p. (37th International Conference on Machine Learning, ICML 2020; vol. PartF168147-10).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review
8 Scopus citations -
Neural Clustering Processes
Pakman, A., Wang, Y., Mitelut, C., Lee, J. & Paninski, L., 1 Jan 2020, In: Proceedings of Machine Learning Research. 119, p. 7455-7465 11 p.Research output: Contribution to journal › Conference article › peer-review
8 Scopus citations -
Neural Permutation Processes
Pakman, A., Wang, Y. & Paninski, L., 1 Jan 2019, In: Proceedings of Machine Learning Research. 118Research output: Contribution to journal › Conference article › peer-review
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Stochastic bouncy particle sampler
Pakman, A., Gilboa, D., Carlson, D. & Paninski, L., 1 Jan 2017, 34th International Conference on Machine Learning, ICML 2017. International Machine Learning Society (IMLS), p. 4186-4208 23 p. (34th International Conference on Machine Learning, ICML 2017; vol. 6).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review
5 Scopus citations
Prizes
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Mitchell Prize
Gabitto, M. (Recipient), Marie-Nelly , H. (Recipient), Pakman, A. (Recipient), Pataki, A. (Recipient), Darzacq, X. (Recipient) & Jordan, M. (Recipient), 2021
Prize
Projects
- 2 Active
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Sampling from Discrete Distributions via Exact Hamiltonian Monte Carlo
Pakman, A. (PI)
1/01/23 → 31/12/26
Project: Research