Aviv Navon

According to our database, Aviv Navon authored at least 16 papers between 2021 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

Multi Task Inverse Reinforcement Learning for Common Sense Reward.

Neta Glazer, Aviv Navon, Aviv Shamsian, Ethan Fetaya

CoRR, 2024

Improved Generalization of Weight Space Networks via Augmentations.

Aviv Shamsian, Aviv Navon, David W. Zhang, Yan Zhang, Ethan Fetaya, Gal Chechik, Haggai Maron

CoRR, 2024

2023

Data Augmentations in Deep Weight Spaces.

Aviv Shamsian, David W. Zhang, Aviv Navon, Yan Zhang, Miltiadis Kofinas, Idan Achituve, Riccardo Valperga, Gertjan J. Burghouts, Efstratios Gavves, Cees G. M. Snoek, Ethan Fetaya, Gal Chechik, Haggai Maron

CoRR, 2023

Combining Language Models For Specialized Domains: A Colorful Approach.

Daniel Eitan, Menachem Pirchi, Neta Glazer, Shai Meital, Gil Ayach, Gidon Krendel, Aviv Shamsian, Aviv Navon, Gill Hetz, Joseph Keshet

CoRR, 2023

Equivariant Deep Weight Space Alignment.

Aviv Navon, Aviv Shamsian, Ethan Fetaya, Gal Chechik, Nadav Dym, Haggai Maron

CoRR, 2023

Open-vocabulary Keyword-spotting with Adaptive Instance Normalization.

Aviv Navon, Aviv Shamsian, Neta Glazer, Gill Hetz, Joseph Keshet

CoRR, 2023

Learning Discrete Weights and Activations Using the Local Reparameterization Trick.

Guy Berger, Aviv Navon, Ethan Fetaya

CoRR, 2023

Auxiliary Learning as an Asymmetric Bargaining Game.

Aviv Shamsian, Aviv Navon, Neta Glazer, Kenji Kawaguchi, Gal Chechik, Ethan Fetaya

Proceedings of the International Conference on Machine Learning, 2023

Equivariant Architectures for Learning in Deep Weight Spaces.

Aviv Navon, Aviv Shamsian, Idan Achituve, Ethan Fetaya, Gal Chechik, Haggai Maron

Proceedings of the International Conference on Machine Learning, 2023

2022

A Study on the Evaluation of Generative Models.

Eyal Betzalel, Coby Penso, Aviv Navon, Ethan Fetaya

CoRR, 2022

Multi-Task Learning as a Bargaining Game.

Aviv Navon, Aviv Shamsian, Idan Achituve, Haggai Maron, Kenji Kawaguchi, Gal Chechik, Ethan Fetaya

Proceedings of the International Conference on Machine Learning, 2022

2021

Personalized Federated Learning With Gaussian Processes.

Idan Achituve, Aviv Shamsian, Aviv Navon, Gal Chechik, Ethan Fetaya

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Personalized Federated Learning using Hypernetworks.

Aviv Shamsian, Aviv Navon, Ethan Fetaya, Gal Chechik

Proceedings of the 38th International Conference on Machine Learning, 2021

GP-Tree: A Gaussian Process Classifier for Few-Shot Incremental Learning.

Idan Achituve, Aviv Navon, Yochai Yemini, Gal Chechik, Ethan Fetaya

Proceedings of the 38th International Conference on Machine Learning, 2021

Learning the Pareto Front with Hypernetworks.

Aviv Navon, Aviv Shamsian, Ethan Fetaya, Gal Chechik

Proceedings of the 9th International Conference on Learning Representations, 2021

Auxiliary Learning by Implicit Differentiation.

Aviv Navon, Idan Achituve, Haggai Maron, Gal Chechik, Ethan Fetaya

Proceedings of the 9th International Conference on Learning Representations, 2021