Publications

Open-vocabulary Keyword-spotting with Adaptive Instance Normalization.
ICASSP, 2024.

Aviv Navon*, Aviv Shamsian*, Neta Glazer, Gill Hetz, Joseph Keshet
[paper]


Equivariant Architectures for Learning in Deep Weight Spaces.
ICML, 2023.
Oral presentation.
Aviv Navon*, Aviv Shamsian*, Idan Achituve, Ethan Fetaya, Gal Chechik, Haggai Maron
[paper] [project page] [video] [poster] [code] [blog] [bibtex]


Auxiliary Learning as an Asymmetric Bargaining Game.
ICML, 2023.
Aviv Shamsian*, Aviv Navon*, Neta Glazer, Kenji Kawaguchi, Gal Chechik, Ethan Fetaya
[paper] [project page] [code] [bibtex]


Multi-Task Learning as a Bargaining Game.
ICML, 2022.
Aviv Navon, Aviv Shamsian, Idan Achituve, Haggai Maron, Kenji Kawaguchi, Gal Chechik, Ethan Fetaya
[paper] [project page] [video] [poster] [code] [bibtex]


Personalized Federated Learning with Gaussian Processes.
NeurIPS, 2021.
Idan Achituve, Aviv Shamsian, Aviv Navon, Gal Chechik, Ethan Fetaya
[paper] [code]


Personalized Federated Learning using Hypernetworks.
ICML, 2021.
Aviv Shamsian*, Aviv Navon*, Ethan Fetaya, Gal Chechik
(* equal contribution)
[paper] [project page] [code] [bibtex]


GP-Tree: A Gaussian Process Classifier for Few-Shot Incremental Learning.
ICML, 2021.
Idan Achituve, Aviv Navon, Yochai Yemini, Gal Chechik, Ethan Fetaya
[paper] [bibtex]


Learning the Pareto Front with Hypernetworks.
ICLR, 2021.
Aviv Navon*, Aviv Shamsian*, Gal Chechik, Ethan Fetaya
(* equal contribution)
[paper] [project page] [video] [poster] [code] [bibtex]


Auxiliary Learning by Implicit Differentiation.
ICLR, 2021.
Aviv Navon*, Idan Achituve*, Haggai Maron, Gal Chechik†, Ethan Fetaya†
(*,† equal contribution)
[paper] [project page] [video] [poster] [code] [bibtex]


Capturing Between-Tasks Covariance and Similarities Using Multivariate Linear Mixed Models.
Electronic Journal of Statistics, 2020.
Aviv Navon, Saharon Rosset
[paper] [code] [bibtex]


Preprint


Equivariant Deep Weight Space Alignment.
Preprint, 2023.
Aviv Navon, Aviv Shamsian, Ethan Fetaya, Gal Chechik, Nadav Dym, Haggai Maron
[paper]


Learning Discrete Weights and Activations Using the Local Reparameterization Trick.
Preprint, 2023.
Guy Berger, Aviv Navon, Ethan Fetaya
[paper]


A Study on the Evaluation of Generative Models.
Preprint, 2022.
Eyal Betzalel, Coby Penso, Aviv Navon, Ethan Fetaya
[paper]