Noam Elata

About Me

I am a Ph.D. graduate of the Electrical and Computer Engineering faculty at the Technion, researching computer vision and machine learning under the supervision of Prof. Michael Elad and Prof. Tomer Michaeli. I am interested in generative models and theoretical deep learning, focusing most of my recent work on diffusion models. I am also interested in neural architectures, attention sparsity, and long video generation. As of summer 2024, I am also a GenAI researcher at Apple in Herzeliya.

Prior to my Ph.D. studies, I received my B.Sc., summa cum laude, in computer engineering from Technion. During my studies, I have worked as a computer vision engineer at Mobileye.

Publications

2026

Shai Yehezkel, Shahar Yadin, Noam Elata, Yaron Ostrovsky-Berman, Bahjat Kawar
Accelerating Text-to-Video Generation with Calibrated Sparse Attention
Preprint 2026

2025

Daniel Ohayon, Itay Lamprecht, Itay Hubara, Israel Cohen, Daniel Soudry, Noam Elata
Block Sparse Flash Attention
Preprint 2025
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Noam Elata*, Hyungjin Chung*, Jong Chul Ye, Tomer Michaeli, Michael Elad
InvFusion: Bridging Supervised and Zero-shot Diffusion for Inverse Problems
NeurIPS 2025 — The 39th Conference on Neural Information Processing Systems
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Noam Elata, Bahjat Kawar, Yaron Ostrovsky-Berman, Miriam Farber, Ron Sokolovsky
Novel View Synthesis with Pixel-Space Diffusion Models
CVPR 2025 — The IEEE/CVF Conference on Computer Vision and Pattern Recognition
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Noam Elata, Tomer Michaeli, Michael Elad
PSC: Posterior Sampling-Based Compression
TMLR 2025 — Transactions on Machine Learning Research
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2024

Shahar Yadin, Noam Elata, Tomer Michaeli
Classification Diffusion Models: Revitalizing Density Ratio Estimation
NeurIPS 2024 — The 38th Conference on Neural Information Processing Systems
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Noam Elata, Tomer Michaeli, Michael Elad
Adaptive Compressed Sensing with Diffusion-Based Posterior Sampling
ECCV 2024 — The 18th European Conference on Computer Vision
☆ Rothschild Academic Excellence Award
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Bahjat Kawar*, Noam Elata*, Tomer Michaeli, Michael Elad
GSURE-Based Diffusion Model Training with Corrupted Data
TMLR 2024 — Transactions on Machine Learning Research
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Noam Elata, Bahjat Kawar, Tomer Michaeli, Michael Elad
Nested Diffusion Processes for Anytime Image Generation
WACV 2024 — The IEEE/CVF Winter Conference on Applications of Computer Vision
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Awards

• NeurIPS Top Reviewer, 2025
• Rothschild Academic Excellence Award, 2024
• Meyer Fellows Prize, 2022
• EMET Excellence Program, 2020–2022
• Alfred and Anna Grey Excellence Scholarship, 2021
• Apple Excellence Award, 2021
• Technion Alumni Scholarship, 2020

Teaching & Program Committee

I have taught the following courses as a TA:

• Generative AI — Diffusion Models (CS236610, CS236759) – Winter 2023–2024 (recorded lectures), Spring 2025
• Deep Learning (ECE046211) – Spring 2023 (projects GitHub)

I have served as a reviewer at the following venues:

• ECCV 2026
• CVPR 2026
• ICML 2026
• NeurIPS 2025 (Top Reviewer)
• ICML 2025
• CVPR 2025
• ICLR 2025
• ECCV 2024

Collaborators

I have had the pleasure to work with:

• Bahjat Kawar
• Shahar Yadin
• Hyungjin Chung
• Jong Chul Ye
• Daniel Soudry
• Israel Cohen
• Roy Ganz
• Hila Manor
• Yaniv Blumenfeld
• Sean Man
• Ron Raphaeli
• Itay Lamprecht
• Daniel Ohayon
• Itay Hubara
• Ido Blayberg
• Ohad Amsalem
• Shai Yehezkel
• Yaron Ostrovsky-Berman
• Miriam Farber
• Ron Sokolovsky