| Neural Network Distiller N Zmora, G Jacob, G Novik https://github.com/IntelLabs/distiller, 2018 | 141* | 2018 |
| Reinforcement Learning Coach I Caspi, G Leibovich, G Novik, S Endrawis https://github.com/IntelLabs/coach, 2017 | 70* | 2017 |
| Constructing deep neural networks by Bayesian network structure learning RY Rohekar, S Nisimov, Y Gurwicz, G Koren, G Novik Advances in Neural Information Processing Systems 31, 2018 | 38 | 2018 |
| Selecting candidate rows for deduplication Y Zinar, E Hudis, Y Orlin, G Novik, Y Gurevich, G Peleg US Patent 8,719,236, 2014 | 24 | 2014 |
| Iterative Causal Discovery in the Possible Presence of Latent Confounders and Selection Bias R Yehezkel Rohekar, S Nisimov, Y Gurwicz, G Novik Advances in Neural Information Processing Systems 34, 2021 | 23 | 2021 |
| Low rank matrix compression T Bar-On, J Subag, Y Fais, J Dreyfuss, G Novik, G Leibovich, T Schwartz, ... US Patent 11,037,330, 2021 | 20 | 2021 |
| Modeling uncertainty by learning a hierarchy of deep neural connections RY Rohekar, Y Gurwicz, S Nisimov, G Novik Advances in Neural Information Processing Systems 32, 2019 | 19 | 2019 |
| Bayesian structure learning by recursive bootstrap RY Rohekar, Y Gurwicz, S Nisimov, G Koren, G Novik Advances in Neural Information Processing Systems 31, 2018 | 18 | 2018 |
| System and method for learning the structure of deep convolutional neural networks G Koren, RYY Rohekar, S Nisimov, G Novik US Patent 11,010,658, 2021 | 15 | 2021 |
| Knowledge based parsing Y Orlin, E Ziklik, G Novik, N Haiby, E Hudis, M Raviv, JI Malka US Patent App. 13/288,942, 2013 | 15 | 2013 |
| Efficient Self-Supervised Data Collection for Offline Robot Learning S Endrawis, G Leibovich, G Jacob, G Novik, A Tamar 2021 IEEE International Conference on Robotics and Automation (ICRA), 2021 | 11 | 2021 |
| Per kernel Kmeans compression for neural networks Y Glesner, G Novik, D Vainbrand, G Leibovich US Patent 11,055,604, 2021 | 8 | 2021 |
| From temporal to contemporaneous iterative causal discovery in the presence of latent confounders RY Rohekar, S Nisimov, Y Gurwicz, G Novik International Conference on Machine Learning, 39939-39950, 2023 | 7 | 2023 |
| Validate on Sim, Detect on Real--Model Selection for Domain Randomization G Leibovich, G Jacob, S Endrawis, G Novik, A Tamar 2022 IEEE International Conference on Robotics and Automation (ICRA), 2021 | 6 | 2021 |
| Online activation compression with k-means G Leibovich, G Novik, Y Glesner US Patent App. 15/720,298, 2019 | 6 | 2019 |
| Improving efficiency and accuracy of causal discovery using a hierarchical wrapper S Nisimov, Y Gurwicz, RY Rohekar, G Novik arXiv preprint arXiv:2107.05001, 2021 | 5 | 2021 |
| CLEAR: Causal explanations from attention in neural recommenders S Nisimov, RY Rohekar, Y Gurwicz, G Koren, G Novik arXiv preprint arXiv:2210.10621, 2022 | 3 | 2022 |
| Learning control by iterative inversion G Leibovich, G Jacob, O Avner, G Novik, A Tamar International Conference on Machine Learning, 19228-19255, 2023 | 2 | 2023 |
| Causal explanation of attention-based neural network output S Nisimov, RYY Rohekar, Y Gurwicz, G Koren, G Novik US Patent App. 18/325,267, 2023 | 1 | 2023 |
| Techniques for determining artificial neural network topologies Y Gurwicz, RYY Rohekar, S Nisimov, G Koren, G Novik US Patent 11,698,930, 2023 | 1 | 2023 |
