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]