| On the universality of invariant networks H Maron, E Fetaya, N Segol, Y Lipman International conference on machine learning, 4363-4371, 2019 | 237 | 2019 |
| On universal equivariant set networks N Segol, Y Lipman arXiv preprint arXiv:1910.02421, 2019 | 62 | 2019 |
| Surface networks via general covers N Haim, N Segol, H Ben-Hamu, H Maron, Y Lipman Proceedings of the IEEE/CVF international conference on computer vision, 632-641, 2019 | 53 | 2019 |
| Set2graph: Learning graphs from sets H Serviansky, N Segol, J Shlomi, K Cranmer, E Gross, H Maron, Y Lipman Advances in Neural Information Processing Systems 33, 22080-22091, 2020 | 40 | 2020 |
| Secondary vertex finding in jets with neural networks J Shlomi, S Ganguly, E Gross, K Cranmer, Y Lipman, H Serviansky, ... The European Physical Journal C 81 (6), 1-12, 2021 | 35 | 2021 |
| Improved convergence guarantees for learning Gaussian mixture models by EM and gradient EM N Segol, B Nadler Electronic journal of statistics 15 (2), 4510-4544, 2021 | 10 | 2021 |
| Secondary Vertex Finding in Jets with Neural Networks (2020) J Shlomi, S Ganguly, E Gross, K Cranmer, Y Lipman, H Serviansky, ... arXiv preprint arXiv:2008.02831, 0 | 4 | |
| Mountnet: Learning an inertial sensor mounting angle with deep neural networks M Freydin, N Sfaradi, N Segol, A Eweida, B Or arXiv preprint arXiv:2212.11120, 2022 | 2 | 2022 |
| Learning Position From Vehicle Vibration Using an Inertial Measurement Unit B Or, N Segol, A Eweida, M Freydin arXiv preprint arXiv:2303.03942, 2023 | 1 | 2023 |
| Deep Learning for Inertial Sensor Alignment M Freydin, N Segol, N Sfaradi, A Eweida, B Or IEEE Sensors Journal, 2024 | | 2024 |
| Set2Graph: Learning Graphs From Sets: Supplementary Material H Serviansky, N Segol, J Shlomi, K Cranmer, E Gross, H Maron, Y Lipman | | |
Niv HaimWeizmann Institute of ScienceZweryfikowany adres z weizmann.ac.il
