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2020 – today
- 2024
[j1]Ohad Amosy, Tamuz Danzig, Ohad Lev, Ely Porat, Gal Chechik, Adi Makmal:
Iteration-Free quantum approximate optimization algorithm using neural networks. Quantum Mach. Intell. 6(2): 38 (2024)- [c4]Ohad Amosy, Tomer Volk, Eilam Shapira, Eyal Ben-David, Roi Reichart, Gal Chechik:
Text2Model: Text-based Model Induction for Zero-shot Image Classification. EMNLP (Findings) 2024: 155-172 - [c3]Ohad Amosy, Gal Eyal, Gal Chechik:
Late to the party? On-demand unlabeled personalized federated learning. WACV 2024: 2173-2182 - 2023
- [c2]Tomer Volk, Eyal Ben-David, Ohad Amosy, Gal Chechik, Roi Reichart:
Example-based Hypernetworks for Multi-source Adaptation to Unseen Domains. EMNLP (Findings) 2023: 9096-9113 - 2022
- [c1]Ohad Amosy, Gal Chechik:
Coupled Training for Multi-Source Domain Adaptation. WACV 2022: 1071-1080 - [i4]Tomer Volk, Eyal Ben-David, Ohad Amosy, Gal Chechik, Roi Reichart:
Example-based Hypernetworks for Out-of-Distribution Generalization. CoRR abs/2203.14276 (2022) - [i3]Ohad Amosy, Tomer Volk, Eyal Ben-David, Roi Reichart, Gal Chechik:
Text2Model: Model Induction for Zero-shot Generalization Using Task Descriptions. CoRR abs/2210.15182 (2022) - 2021
- [i2]Ohad Amosy, Gal Eyal, Gal Chechik:
Inference-Time Personalized Federated Learning. CoRR abs/2111.08356 (2021) - 2020
- [i1]Ohad Amosy, Gal Chechik:
Teacher-Student Consistency For Multi-Source Domain Adaptation. CoRR abs/2010.10054 (2020)
Coauthor Index
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