Ethan Fetaya

Publication Activity (10 Years)

Years Active: 2011-2024
Publications (10 Years): 71

Top Topics

Constraint Logic Programming

Autonomous Driving

Program Synthesis

Gaussian Process

Top Venues

Publications

Yochai Yemini, Aviv Shamsian, Lior Bracha, Sharon Gannot, Ethan Fetaya
LipVoicer: Generating Speech from Silent Videos Guided by Lip Reading. ICLR (2024)
Idan Achituve, Idit Diamant, Arnon Netzer, Gal Chechik, Ethan Fetaya
Bayesian Uncertainty for Gradient Aggregation in Multi-Task Learning. CoRR (2024)
Aviv Shamsian, Aviv Navon, David W. Zhang, Yan Zhang, Ethan Fetaya, Gal Chechik, Haggai Maron
Improved Generalization of Weight Space Networks via Augmentations. CoRR (2024)
Neta Glazer, Aviv Navon, Aviv Shamsian, Ethan Fetaya
Multi Task Inverse Reinforcement Learning for Common Sense Reward. CoRR (2024)
Aviv Shamsian, Aviv Navon, Neta Glazer, Kenji Kawaguchi, Gal Chechik, Ethan Fetaya
Auxiliary Learning as an Asymmetric Bargaining Game. CoRR (2023)
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
Data Augmentations in Deep Weight Spaces. CoRR (2023)
Aviv Shamsian, Aviv Navon, Neta Glazer, Kenji Kawaguchi, Gal Chechik, Ethan Fetaya
Auxiliary Learning as an Asymmetric Bargaining Game. ICML (2023)
Aviv Navon, Aviv Shamsian, Idan Achituve, Ethan Fetaya, Gal Chechik, Haggai Maron
Equivariant Architectures for Learning in Deep Weight Spaces. ICML (2023)
Lior Bracha, Eitan Shaar, Aviv Shamsian, Ethan Fetaya, Gal Chechik
DisCLIP: Open-Vocabulary Referring Expression Generation. CoRR (2023)
Hila Levi, Guy Heller, Dan Levi, Ethan Fetaya
Object-Centric Open-Vocabulary Image-Retrieval with Aggregated Features. CoRR (2023)
Aviv Navon, Aviv Shamsian, Idan Achituve, Ethan Fetaya, Gal Chechik, Haggai Maron
Equivariant Architectures for Learning in Deep Weight Spaces. CoRR (2023)
Idan Achituve, Gal Chechik, Ethan Fetaya
Guided Deep Kernel Learning. CoRR (2023)
Idan Achituve, Gal Chechik, Ethan Fetaya
Guided Deep Kernel Learning. UAI (2023)
Yochai Yemini, Aviv Shamsian, Lior Bracha, Sharon Gannot, Ethan Fetaya
LipVoicer: Generating Speech from Silent Videos Guided by Lip Reading. CoRR (2023)
Idan Achituve, Wenbo Wang, Ethan Fetaya, Amir Leshem
Communication Efficient Distributed Learning Over Wireless Channels. IEEE Signal Process. Lett. 30 (2023)
Guy Heller, Ethan Fetaya
Can Stochastic Gradient Langevin Dynamics Provide Differential Privacy for Deep Learning? SaTML (2023)
Lior Bracha, Eitan Shaar, Aviv Shamsian, Ethan Fetaya, Gal Chechik
DisCLIP: Open-Vocabulary Referring Expression Generation. BMVC (2023)
Hila Levi, Guy Heller, Dan Levi, Ethan Fetaya
Object-Centric Open-Vocabulary Image Retrieval with Aggregated Features. BMVC (2023)
Aviv Navon, Aviv Shamsian, Ethan Fetaya, Gal Chechik, Nadav Dym, Haggai Maron
Equivariant Deep Weight Space Alignment. CoRR (2023)
Guy Berger, Aviv Navon, Ethan Fetaya
Learning Discrete Weights and Activations Using the Local Reparameterization Trick. CoRR (2023)
Ariel Lapid, Idan Achituve, Lior Bracha, Ethan Fetaya
GD-VDM: Generated Depth for better Diffusion-based Video Generation. CoRR (2023)
Coby Penso, Idan Achituve, Ethan Fetaya
Functional Ensemble Distillation. NeurIPS (2022)
Dan Levi, Liran Gispan, Niv Giladi, Ethan Fetaya
Evaluating and Calibrating Uncertainty Prediction in Regression Tasks. Sensors 22 (15) (2022)
Aviv Navon, Aviv Shamsian, Idan Achituve, Haggai Maron, Kenji Kawaguchi, Gal Chechik, Ethan Fetaya
Multi-Task Learning as a Bargaining Game. CoRR (2022)
Idan Achituve, Wenbo Wang, Ethan Fetaya, Amir Leshem
Communication Efficient Distributed Learning over Wireless Channels. CoRR (2022)
Aviv Navon, Aviv Shamsian, Idan Achituve, Haggai Maron, Kenji Kawaguchi, Gal Chechik, Ethan Fetaya
Multi-Task Learning as a Bargaining Game. ICML (2022)
Coby Penso, Idan Achituve, Ethan Fetaya
Functional Ensemble Distillation. CoRR (2022)
Eyal Betzalel, Coby Penso, Aviv Navon, Ethan Fetaya
A Study on the Evaluation of Generative Models. CoRR (2022)
Yochai Yemini, Ethan Fetaya, Haggai Maron, Sharon Gannot
Scene-Agnostic Multi-Microphone Speech Dereverberation. Interspeech (2021)
Aviv Navon, Aviv Shamsian, Ethan Fetaya, Gal Chechik
Learning the Pareto Front with Hypernetworks. ICLR (2021)
Aviv Shamsian, Aviv Navon, Ethan Fetaya, Gal Chechik
Personalized Federated Learning using Hypernetworks. CoRR (2021)
Aviv Navon, Idan Achituve, Haggai Maron, Gal Chechik, Ethan Fetaya
Auxiliary Learning by Implicit Differentiation. ICLR (2021)
Idan Achituve, Aviv Navon, Yochai Yemini, Gal Chechik, Ethan Fetaya
GP-Tree: A Gaussian Process Classifier for Few-Shot Incremental Learning. CoRR (2021)
Haggai Maron, Or Litany, Gal Chechik, Ethan Fetaya
On Learning Sets of Symmetric Elements (Extended Abstract). IJCAI (2021)
Aviv Shamsian, Aviv Navon, Ethan Fetaya, Gal Chechik
Personalized Federated Learning using Hypernetworks. ICML (2021)
Gilad Yehudai, Ethan Fetaya, Eli A. Meirom, Gal Chechik, Haggai Maron
From Local Structures to Size Generalization in Graph Neural Networks. ICML (2021)
Idan Achituve, Aviv Shamsian, Aviv Navon, Gal Chechik, Ethan Fetaya
Personalized Federated Learning with Gaussian Processes. CoRR (2021)
Idan Achituve, Aviv Navon, Yochai Yemini, Gal Chechik, Ethan Fetaya
GP-Tree: A Gaussian Process Classifier for Few-Shot Incremental Learning. ICML (2021)
Idan Achituve, Aviv Shamsian, Aviv Navon, Gal Chechik, Ethan Fetaya
Personalized Federated Learning With Gaussian Processes. NeurIPS (2021)
Guy Heller, Ethan Fetaya
Can Stochastic Gradient Langevin Dynamics Provide Differential Privacy for Deep Learning? CoRR (2021)
Gilad Yehudai, Ethan Fetaya, Eli A. Meirom, Gal Chechik, Haggai Maron
On Size Generalization in Graph Neural Networks. CoRR (2020)
Ethan Fetaya, Yonatan Lifshitz, Elad Aaron, Shai Gordin
Restoration of fragmentary Babylonian texts using recurrent neural networks. Proc. Natl. Acad. Sci. USA 117 (37) (2020)
Yochai Yemini, Ethan Fetaya, Haggai Maron, Sharon Gannot
Position-Agnostic Multi-Microphone Speech Dereverberation. CoRR (2020)
Haggai Maron, Or Litany, Gal Chechik, Ethan Fetaya
On Learning Sets of Symmetric Elements. CoRR (2020)
Aviv Navon, Aviv Shamsian, Gal Chechik, Ethan Fetaya
Learning the Pareto Front with Hypernetworks. CoRR (2020)
Ethan Fetaya, Yonatan Lifshitz, Elad Aaron, Shai Gordin
Restoration of Fragmentary Babylonian Texts Using Recurrent Neural Networks. CoRR (2020)
Ethan Fetaya, Jörn-Henrik Jacobsen, Will Grathwohl, Richard S. Zemel
Understanding the Limitations of Conditional Generative Models. ICLR (2020)
Haggai Maron, Or Litany, Gal Chechik, Ethan Fetaya
On Learning Sets of Symmetric Elements. ICML (2020)
Aviv Navon, Idan Achituve, Haggai Maron, Gal Chechik, Ethan Fetaya
Auxiliary Learning by Implicit Differentiation. CoRR (2020)
Dan Levi, Liran Gispan, Niv Giladi, Ethan Fetaya
Evaluating and Calibrating Uncertainty Prediction in Regression Tasks. CoRR (2019)
Haggai Maron, Ethan Fetaya, Nimrod Segol, Yaron Lipman
On the Universality of Invariant Networks. CoRR (2019)
Mengye Ren, Renjie Liao, Ethan Fetaya, Richard S. Zemel
Incremental Few-Shot Learning with Attention Attractor Networks. NeurIPS (2019)
Haggai Maron, Ethan Fetaya, Nimrod Segol, Yaron Lipman
On the Universality of Invariant Networks. ICML (2019)
KiJung Yoon, Renjie Liao, Yuwen Xiong, Lisa Zhang, Ethan Fetaya, Raquel Urtasun, Richard S. Zemel, Xaq Pitkow
Inference in Probabilistic Graphical Models by Graph Neural Networks. ACSSC (2019)
Ethan Fetaya, Jörn-Henrik Jacobsen, Richard S. Zemel
Conditional Generative Models are not Robust. CoRR (2019)
KiJung Yoon, Renjie Liao, Yuwen Xiong, Lisa Zhang, Ethan Fetaya, Raquel Urtasun, Richard S. Zemel, Xaq Pitkow
Inference in probabilistic graphical models by Graph Neural Networks. ICLR (Workshop) (2018)
Lisa Zhang, Gregory Rosenblatt, Ethan Fetaya, Renjie Liao, William E. Byrd, Matthew Might, Raquel Urtasun, Richard S. Zemel
Neural Guided Constraint Logic Programming for Program Synthesis. NeurIPS (2018)
Thomas N. Kipf, Ethan Fetaya, Kuan-Chieh Wang, Max Welling, Richard S. Zemel
Neural Relational Inference for Interacting Systems. CoRR (2018)
KiJung Yoon, Renjie Liao, Yuwen Xiong, Lisa Zhang, Ethan Fetaya, Raquel Urtasun, Richard S. Zemel, Xaq Pitkow
Inference in Probabilistic Graphical Models by Graph Neural Networks. CoRR (2018)
Thomas N. Kipf, Ethan Fetaya, Kuan-Chieh Wang, Max Welling, Richard S. Zemel
Neural Relational Inference for Interacting Systems. ICML (2018)
Oran Shayer, Dan Levi, Ethan Fetaya
Learning Discrete Weights Using the Local Reparameterization Trick. ICLR (Poster) (2018)
Renjie Liao, Yuwen Xiong, Ethan Fetaya, Lisa Zhang, KiJung Yoon, Xaq Pitkow, Raquel Urtasun, Richard S. Zemel
Reviving and Improving Recurrent Back-Propagation. ICML (2018)
Lisa Zhang, Gregory Rosenblatt, Ethan Fetaya, Renjie Liao, William E. Byrd, Matthew Might, Raquel Urtasun, Richard S. Zemel
Neural Guided Constraint Logic Programming for Program Synthesis. CoRR (2018)
Mengye Ren, Renjie Liao, Ethan Fetaya, Richard S. Zemel
Incremental Few-Shot Learning with Attention Attractor Networks. CoRR (2018)
Lisa Zhang, Gregory Rosenblatt, Ethan Fetaya, Renjie Liao, William E. Byrd, Raquel Urtasun, Richard S. Zemel
Leveraging Constraint Logic Programming for Neural Guided Program Synthesis. ICLR (Workshop) (2018)
Renjie Liao, Yuwen Xiong, Ethan Fetaya, Lisa Zhang, KiJung Yoon, Xaq Pitkow, Raquel Urtasun, Richard S. Zemel
Reviving and Improving Recurrent Back-Propagation. CoRR (2018)
Noa Garnett, Shai Silberstein, Shaul Oron, Ethan Fetaya, Uri Verner, Ariel Ayash, Vlad Goldner, Rafi Cohen, Kobi Horn, Dan Levi
Real-Time Category-Based and General Obstacle Detection for Autonomous Driving. ICCV Workshops (2017)
Oran Shayer, Dan Levi, Ethan Fetaya
Learning Discrete Weights Using the Local Reparameterization Trick. CoRR (2017)
Ita Lifshitz, Ethan Fetaya, Shimon Ullman
Human Pose Estimation using Deep Consensus Voting. CoRR (2016)
Ariel Jaffe, Ethan Fetaya, Boaz Nadler, Tingting Jiang, Yuval Kluger
Unsupervised Ensemble Learning with Dependent Classifiers. AISTATS (2016)
Ita Lifshitz, Ethan Fetaya, Shimon Ullman
Human Pose Estimation Using Deep Consensus Voting. ECCV (2) (2016)
Dan Levi, Noa Garnett, Ethan Fetaya
StixelNet: A Deep Convolutional Network for Obstacle Detection and Road Segmentation. BMVC (2015)
Ethan Fetaya, Ohad Shamir, Shimon Ullman
Graph Approximation and Clustering on a Budget. AISTATS (2015)
Ethan Fetaya, Shimon Ullman
Learning Local Invariant Mahalanobis Distances. ICML (2015)
Ariel Jaffe, Ethan Fetaya, Boaz Nadler, Tingting Jiang, Yuval Kluger
Unsupervised Ensemble Learning with Dependent Classifiers. CoRR (2015)
Ethan Fetaya, Shimon Ullman
Learning Local Invariant Mahalanobis Distances. CoRR (2015)
Ethan Fetaya, Ohad Shamir, Shimon Ullman
Graph Approximation and Clustering on a Budget. CoRR (2014)
Ethan Fetaya
Homological Error Correcting Codes and Systolic Geometry CoRR (2011)