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Ethan Fetaya

30 papers · 2015–2026 · 8 conferences · across top CS/AI conferences

Achievements

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+13 more ↓ 🧭 Keyword Pioneer 🌍 Conference Polyglot (7) πŸ—ΊοΈ Taxonomy Completionist (10) πŸŒ‰ Interdisciplinary Bridge πŸƒ Academic Marathon (10)
πŸƒ Academic Marathon (10) 🐝 Cross-Pollinator (15) 🌈 Renaissance Researcher (7) πŸ† Keyword Champion (2) πŸ† Grand Slam 🀝 Dynamic Duo (15) πŸ‘‘ Triple Crown πŸ—ƒοΈ Keyword Collector (98) πŸ“ˆ Trend Setter πŸ’Ž Century Club (29) πŸ”₯ Unstoppable (8) ⚑ Prolific Year (8) πŸš€ Conference Pioneer

Conferences

ICML (15) ICLR (5) NIPS (4) AISTATS (2) AAAI (1) IJCAI (1) INTERSPEECH (1) UAI (1)

Top co-authors

Gal Chechik (15) Aviv Navon (11) Aviv Shamsian (10) Haggai Maron (10) Idan Achituve (9) Richard Zemel (5) Yochai Yemini (3) Renjie Liao (3) Neta Glazer (2) Lisa Zhang (2)

Keywords

graph neural network (4) deep kernel learning (3) unsupervised learning (2) neural network (2) bayesian inference (2) few-shot learning (2) bargaining game (2) gaussian process (2) set learning (2) symmetric element (2) uncertainty estimation (2) multi-task learning (2) permutation invariance (2) incremental learning (2) self-supervised learning (1) uncertainty quantification (1) graph classification (1) game theory (1) program synthesis (1) ensemble learning (1)

Papers

Beyond Transcription: Mechanistic Interpretability in ASR AAAI 2026 Inverse Problem Sampling in Latent Space Using Sequential Monte Carlo ICML 2025 Equivariant Deep Weight Space Alignment ICML 2024 Bayesian Uncertainty for Gradient Aggregation in Multi-Task Learning ICML 2024 LipVoicer: Generating Speech from Silent Videos Guided by Lip Reading ICLR 2024 Improved Generalization of Weight Space Networks via Augmentations ICML 2024 Guided Deep Kernel Learning UAI 2023 Equivariant Architectures for Learning in Deep Weight Spaces ICML 2023 Auxiliary Learning as an Asymmetric Bargaining Game ICML 2023 Functional Ensemble Distillation NIPS 2022 Multi-Task Learning as a Bargaining Game ICML 2022 From Local Structures to Size Generalization in Graph Neural Networks ICML 2021 Personalized Federated Learning With Gaussian Processes NIPS 2021 Scene-Agnostic Multi-Microphone Speech Dereverberation INTERSPEECH 2021 On Learning Sets of Symmetric Elements (Extended Abstract) IJCAI 2021 Learning the Pareto Front with Hypernetworks ICLR 2021 Auxiliary Learning by Implicit Differentiation ICLR 2021 GP-Tree: A Gaussian Process Classifier for Few-Shot Incremental Learning ICML 2021 Personalized Federated Learning using Hypernetworks ICML 2021 On Learning Sets of Symmetric Elements ICML 2020 Understanding the Limitations of Conditional Generative Models ICLR 2020 Incremental Few-Shot Learning with Attention Attractor Networks NIPS 2019 On the Universality of Invariant Networks ICML 2019 Neural Relational Inference for Interacting Systems ICML 2018 Learning Discrete Weights Using the Local Reparameterization Trick ICLR 2018 Neural Guided Constraint Logic Programming for Program Synthesis NIPS 2018 Reviving and Improving Recurrent Back-Propagation ICML 2018 Unsupervised Ensemble Learning with Dependent Classifiers AISTATS 2016 Graph Approximation and Clustering on a Budget AISTATS 2015 Learning Local Invariant Mahalanobis Distances ICML 2015