| Neural relational inference for interacting systems T Kipf, E Fetaya, KC Wang, M Welling, R Zemel International Conference on Machine Learning, 2018 | 1212 | 2018 |
| Personalized federated learning using hypernetworks A Shamsian, A Navon, E Fetaya, G Chechik International conference on machine learning, 9489-9502, 2021 | 522 | 2021 |
| On the Universality of Invariant Networks H Maron, E Fetaya, N Segol, Y Lipman International Conference on Machine Learning, 2019 | 328 | 2019 |
| Multi-task learning as a bargaining game A Navon, A Shamsian, I Achituve, H Maron, K Kawaguchi, G Chechik, ... arXiv preprint arXiv:2202.01017, 2022 | 266 | 2022 |
| Incremental few-shot learning with attention attractor networks M Ren, R Liao, E Fetaya, R Zemel Advances in neural information processing systems 32, 2019 | 226 | 2019 |
| Evaluating and calibrating uncertainty prediction in regression tasks D Levi, L Gispan, N Giladi, E Fetaya Sensors 22 (15), 5540, 2022 | 224 | 2022 |
| Atoms of recognition in human and computer vision S Ullman, L Assif, E Fetaya, D Harari Proceedings of the National Academy of Sciences 113 (10), 2744-2749, 2016 | 218 | 2016 |
| Human pose estimation using deep consensus voting I Lifshitz, E Fetaya, S Ullman European conference on computer vision, 246-260, 2016 | 215 | 2016 |
| Learning the pareto front with hypernetworks A Navon, A Shamsian, G Chechik, E Fetaya arXiv preprint arXiv:2010.04104, 2020 | 210 | 2020 |
| StixelNet: A Deep Convolutional Network for Obstacle Detection and Road Segmentation. D Levi, N Garnett, E Fetaya BMVC, 109.1-109.12, 2015 | 210 | 2015 |
| From local structures to size generalization in graph neural networks G Yehudai, E Fetaya, E Meirom, G Chechik, H Maron International Conference on Machine Learning, 11975-11986, 2021 | 196 | 2021 |
| Learning discrete weights using the local reparameterization trick O Shayer, D Levi, E Fetaya International Conference on Representation Learning, 2017 | 175 | 2017 |
| Reviving and improving recurrent back-propagation R Liao, Y Xiong, E Fetaya, L Zhang, KJ Yoon, X Pitkow, R Urtasun, ... International conference on machine learning, 3082-3091, 2018 | 169 | 2018 |
| On learning sets of symmetric elements H Maron, O Litany, G Chechik, E Fetaya International conference on machine learning, 6734-6744, 2020 | 159 | 2020 |
| Personalized federated learning with gaussian processes I Achituve, A Shamsian, A Navon, G Chechik, E Fetaya Advances in Neural Information Processing Systems 34, 8392-8406, 2021 | 154 | 2021 |
| Geometric deep optical sensing S Yuan, C Ma, E Fetaya, T Mueller, D Naveh, F Zhang, F Xia Science 379 (6637), eade1220, 2023 | 130 | 2023 |
| Inference in probabilistic graphical models by graph neural networks KJ Yoon, R Liao, Y Xiong, L Zhang, E Fetaya, R Urtasun, R Zemel, ... 2019 53rd Asilomar Conference on Signals, Systems, and Computers, 868-875, 2019 | 128 | 2019 |
| Real-time category-based and general obstacle detection for autonomous driving N Garnett, S Silberstein, S Oron, E Fetaya, U Verner, A Ayash, V Goldner, ... Proceedings of the IEEE International Conference on computer vision …, 2017 | 125 | 2017 |
| Equivariant architectures for learning in deep weight spaces A Navon, A Shamsian, I Achituve, E Fetaya, G Chechik, H Maron International Conference on Machine Learning, 25790-25816, 2023 | 101 | 2023 |
| A study on the evaluation of generative models E Betzalel, C Penso, A Navon, E Fetaya arXiv preprint arXiv:2206.10935, 2022 | 79 | 2022 |
Haggai MaronAssistant Professor at the Technion, Research Scientist at NVIDIA ResearchVerified email at technion.ac.il
