Nir Shavit

Professor

1986 …2021

Research activity per year

If you made any changes in Pure these will be visible here soon.

Fingerprint

Dive into the research topics where Nir Shavit is active. These topic labels come from the works of this person. Together they form a unique fingerprint.
  • 1 Similar Profiles

Network

Recent external collaboration on country/territory level. Dive into details by clicking on the dots or
  • Connectomes across development reveal principles of brain maturation

    Witvliet, D., Mulcahy, B., Mitchell, J. K., Meirovitch, Y., Berger, D. R., Wu, Y., Liu, Y., Koh, W. X., Parvathala, R., Holmyard, D., Schalek, R. L., Shavit, N., Chisholm, A. D., Lichtman, J. W., Samuel, A. D. T. & Zhen, M., 12 Aug 2021, In: Nature. 596, 7871, p. 257-261 5 p.

    Research output: Contribution to journalArticlepeer-review

  • HDMapGen: A Hierarchical Graph Generative Model of High Definition Maps

    Mi, L., Zhao, H., Nash, C., Jin, X., Gao, J., Sun, C., Schmid, C., Shavit, N., Chai, Y. & Anguelov, D., 2021, Proceedings - 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2021. IEEE Computer Society, p. 4225-4234 10 p. (Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition).

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

  • A complexity-based classification for multiprocessor synchronization

    Ellen, F., Gelashvili, R., Shavit, N. & Zhu, L., 1 Apr 2020, In: Distributed Computing. 33, 2, p. 125-144 20 p.

    Research output: Contribution to journalArticlepeer-review

  • Inducing and exploiting activation sparsity for fast neural network inference

    Kurtz, M., Kopinsky, J., Gelashvili, R., Matveev, A., Carr, J., Goin, M., Leiserson, W., Moore, S., Nell, B., Shavit, N. & Alistarh, D., 2020, 37th International Conference on Machine Learning, ICML 2020. Daume, H. & Singh, A. (eds.). International Machine Learning Society (IMLS), p. 5489-5499 11 p. (37th International Conference on Machine Learning, ICML 2020; vol. PartF168147-8).

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

  • Learning Guided Electron Microscopy with Active Acquisition

    Mi, L., Wang, H., Meirovitch, Y., Schalek, R., Turaga, S. C., Lichtman, J. W., Samuel, A. D. T. & Shavit, N., 2020, Medical Image Computing and Computer Assisted Intervention – MICCAI 2020 - 23rd International Conference, Proceedings. Martel, A. L., Abolmaesumi, P., Stoyanov, D., Mateus, D., Zuluaga, M. A., Zhou, S. K., Racoceanu, D. & Joskowicz, L. (eds.). Springer Science and Business Media Deutschland GmbH, p. 77-87 11 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 12265 LNCS).

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