Eliahu Horwitz

According to our database, Eliahu Horwitz authored at least 20 papers between 2020 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2026

Discovering Hidden Gems in Model Repositories.

Jonathan Kahana, Eliahu Horwitz, Yedid Hoshen

CoRR, January, 2026

2025

Charting and Navigating Hugging Face's Model Atlas.

Eliahu Horwitz, Nitzan Kurer, Jonathan Kahana, Liel Amar, Yedid Hoshen

CoRR, March, 2025

Can this Model Also Recognize Dogs? Zero-Shot Model Search from Weights.

Jonathan Kahana, Or Nathan, Eliahu Horwitz, Yedid Hoshen

CoRR, February, 2025

Distilling Datasets Into Less Than One Image.

Asaf Shul, Eliahu Horwitz, Yedid Hoshen

Trans. Mach. Learn. Res., 2025

We Should Chart an Atlas of All the World's Models.

Eliahu Horwitz, Nitzan Kurer, Jonathan Kahana, Liel Amar, Yedid Hoshen

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2025, 2025

Deep Linear Probe Generators for Weight Space Learning.

Jonathan Kahana, Eliahu Horwitz, Imri Shuval, Yedid Hoshen

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

Unsupervised Model Tree Heritage Recovery.

Eliahu Horwitz, Asaf Shul, Yedid Hoshen

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

Learning on Model Weights using Tree Experts.

Eliahu Horwitz, Bar Cavia, Jonathan Kahana, Yedid Hoshen

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2025

2024

Representing Model Weights with Language using Tree Experts.

Eliahu Horwitz, Bar Cavia, Jonathan Kahana, Yedid Hoshen

CoRR, 2024

Dataset Size Recovery from LoRA Weights.

Mohammad Salama, Jonathan Kahana, Eliahu Horwitz, Yedid Hoshen

CoRR, 2024

Real-Time Deepfake Detection in the Real-World.

Bar Cavia, Eliahu Horwitz, Tal Reiss, Yedid Hoshen

CoRR, 2024

On the Origin of Llamas: Model Tree Heritage Recovery.

Eliahu Horwitz, Asaf Shul, Yedid Hoshen

CoRR, 2024

Recovering the Pre-Fine-Tuning Weights of Generative Models.

Eliahu Horwitz, Jonathan Kahana, Yedid Hoshen

Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023

Dreamix: Video Diffusion Models are General Video Editors.

Eyal Molad, Eliahu Horwitz, Dani Valevski, Alex Rav-Acha, Yossi Matias, Yael Pritch, Yaniv Leviathan, Yedid Hoshen

CoRR, 2023

Back to the Feature: Classical 3D Features are (Almost) All You Need for 3D Anomaly Detection.

Eliahu Horwitz, Yedid Hoshen

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

2022

Conffusion: Confidence Intervals for Diffusion Models.

Eliahu Horwitz, Yedid Hoshen

CoRR, 2022

An Empirical Investigation of 3D Anomaly Detection and Segmentation.

Eliahu Horwitz, Yedid Hoshen

CoRR, 2022

Anomaly Detection Requires Better Representations.

Tal Reiss, Niv Cohen, Eliahu Horwitz, Ron Abutbul, Yedid Hoshen

Proceedings of the Computer Vision - ECCV 2022 Workshops, 2022

2021

Image Shape Manipulation from a Single Augmented Training Sample.

Yael Vinker, Eliahu Horwitz, Nir Zabari, Yedid Hoshen

Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

2020

Deep Single Image Manipulation.

Yael Vinker, Eliahu Horwitz, Nir Zabari, Yedid Hoshen

CoRR, 2020