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Eliahu Horwitz
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2020 – today
- 2025
[j1]Asaf Shul, Eliahu Horwitz, Yedid Hoshen:
Distilling Datasets Into Less Than One Image. Trans. Mach. Learn. Res. 2025 (2025)
[c7]Eliahu Horwitz, Bar Cavia, Jonathan Kahana, Yedid Hoshen:
Learning on Model Weights using Tree Experts. CVPR 2025: 20468-20478
[c6]Eliahu Horwitz, Asaf Shul, Yedid Hoshen:
Unsupervised Model Tree Heritage Recovery. ICLR 2025
[c5]Jonathan Kahana, Eliahu Horwitz, Imri Shuval, Yedid Hoshen:
Deep Linear Probe Generators for Weight Space Learning. ICLR 2025
[i14]Jonathan Kahana, Or Nathan, Eliahu Horwitz, Yedid Hoshen:
Can this Model Also Recognize Dogs? Zero-Shot Model Search from Weights. CoRR abs/2502.09619 (2025)
[i13]Eliahu Horwitz, Nitzan Kurer, Jonathan Kahana, Liel Amar, Yedid Hoshen:
Charting and Navigating Hugging Face's Model Atlas. CoRR abs/2503.10633 (2025)- 2024
[c4]Eliahu Horwitz, Jonathan Kahana, Yedid Hoshen:
Recovering the Pre-Fine-Tuning Weights of Generative Models. ICML 2024
[i12]Eliahu Horwitz, Jonathan Kahana, Yedid Hoshen:
Recovering the Pre-Fine-Tuning Weights of Generative Models. CoRR abs/2402.10208 (2024)
[i11]Asaf Shul, Eliahu Horwitz, Yedid Hoshen:
Distilling Datasets Into Less Than One Image. CoRR abs/2403.12040 (2024)
[i10]Eliahu Horwitz, Asaf Shul, Yedid Hoshen:
On the Origin of Llamas: Model Tree Heritage Recovery. CoRR abs/2405.18432 (2024)
[i9]Bar Cavia, Eliahu Horwitz, Tal Reiss, Yedid Hoshen:
Real-Time Deepfake Detection in the Real-World. CoRR abs/2406.09398 (2024)
[i8]Mohammad Salama, Jonathan Kahana, Eliahu Horwitz, Yedid Hoshen:
Dataset Size Recovery from LoRA Weights. CoRR abs/2406.19395 (2024)
[i7]Jonathan Kahana, Eliahu Horwitz, Imri Shuval, Yedid Hoshen:
Deep Linear Probe Generators for Weight Space Learning. CoRR abs/2410.10811 (2024)
[i6]Eliahu Horwitz, Bar Cavia, Jonathan Kahana, Yedid Hoshen:
Representing Model Weights with Language using Tree Experts. CoRR abs/2410.13569 (2024)- 2023
[c3]Eliahu Horwitz, Yedid Hoshen:
Back to the Feature: Classical 3D Features are (Almost) All You Need for 3D Anomaly Detection. CVPR Workshops 2023: 2968-2977
[i5]Eyal Molad, Eliahu Horwitz, Dani Valevski, Alex Rav-Acha, Yossi Matias, Yael Pritch, Yaniv Leviathan, Yedid Hoshen:
Dreamix: Video Diffusion Models are General Video Editors. CoRR abs/2302.01329 (2023)- 2022
[c2]Tal Reiss, Niv Cohen, Eliahu Horwitz, Ron Abutbul, Yedid Hoshen:
Anomaly Detection Requires Better Representations. ECCV Workshops (4) 2022: 56-68
[i4]Eliahu Horwitz, Yedid Hoshen:
An Empirical Investigation of 3D Anomaly Detection and Segmentation. CoRR abs/2203.05550 (2022)
[i3]Tal Reiss, Niv Cohen, Eliahu Horwitz, Ron Abutbul, Yedid Hoshen:
Anomaly Detection Requires Better Representations. CoRR abs/2210.10773 (2022)
[i2]Eliahu Horwitz, Yedid Hoshen:
Conffusion: Confidence Intervals for Diffusion Models. CoRR abs/2211.09795 (2022)- 2021
[c1]Yael Vinker, Eliahu Horwitz, Nir Zabari, Yedid Hoshen:
Image Shape Manipulation from a Single Augmented Training Sample. ICCV 2021: 13749-13758- 2020
[i1]Yael Vinker, Eliahu Horwitz, Nir Zabari, Yedid Hoshen:
Deep Single Image Manipulation. CoRR abs/2007.01289 (2020)
Coauthor Index

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