Idan Achituve
Cited by
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Self-supervised learning for domain adaptation on point clouds
I Achituve, H Maron, G Chechik
Proceedings of the IEEE/CVF winter conference on applications of computer…, 2021
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
Multi-task learning as a bargaining game
A Navon, A Shamsian, I Achituve, H Maron, K Kawaguchi, G Chechik, ...
International Conference on Machine Learning, 2022
Auxiliary learning by implicit differentiation
A Navon, I Achituve, H Maron, G Chechik, E Fetaya
International Conference on Learning Representations, 2020
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
GP-Tree: A Gaussian process classifier for few-shot incremental learning
I Achituve, A Navon, Y Yemini, G Chechik, E Fetaya
International Conference on Machine Learning, 54-65, 2021
Interpretable online banking fraud detection based on hierarchical attention mechanism
I Achituve, S Kraus, J Goldberger
2019 IEEE 29th international workshop on machine learning for signal…, 2019
Gd-vdm: Generated depth for better diffusion-based video generation
A Lapid, I Achituve, L Bracha, E Fetaya
arXiv preprint arXiv:2306.11173, 2023
Guided Deep Kernel Learning
I Achituve, G Chechik, E Fetaya
Proceedings of the Thirty-Ninth Conference on Uncertainty in Artificial…, 2023
Functional Ensemble Distillation
C Penso, I Achituve, E Fetaya
Advances in Neural Information Processing Systems, 2022
Data Augmentations in Deep Weight Spaces
A Shamsian, DW Zhang, A Navon, Y Zhang, M Kofinas, I Achituve, ...
arXiv preprint arXiv:2311.08851, 2023
Communication efficient distributed learning over wireless channels
I Achituve, W Wang, E Fetaya, A Leshem
IEEE Signal Processing Letters, 2023
Lay-A-Scene: Personalized 3D Object Arrangement Using Text-to-Image Priors
O Rahamim, H Segev, I Achituve, Y Atzmon, Y Kasten, G Chechik
arXiv preprint arXiv:2406.00687, 2024
Bayesian Uncertainty for Gradient Aggregation in Multi-Task Learning
I Achituve, I Diamant, A Netzer, G Chechik, E Fetaya
arXiv preprint arXiv:2402.04005, 2024
De-Confusing Pseudo-Labels in Source-Free Domain Adaptation
I Diamant, I Achituve, A Netzer
arXiv preprint arXiv:2401.01650, 2024
2021 IEEE Winter Conference on Applications of Computer Vision (WACV)| 978-1-6654-0477-8/20/$31.00 2021 IEEE| DOI: 10.1109/WACV48630. 2021.00411
I Achituve, Y Agrawal, AB Albu, W An, T Anderson, S Appalaraju, ...
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Articles 1–16