Deep Nearest Neighbor Anomaly Detection. - Liron Bergman; Niv Cohen; Yedid Hoshen (CoRR, 2020)

Sub-Image Anomaly Detection with Deep Pyramid Correspondences. - Niv Cohen; Yedid Hoshen (CoRR, 2020)

PANDA - Adapting Pretrained Features for Anomaly Detection. - Tal Reiss; Niv Cohen; Liron Bergman; Yedid Hoshen (CoRR, 2020)

PANDA: Adapting Pretrained Features for Anomaly Detection and Segmentation. - Tal Reiss; Niv Cohen; Liron Bergman; Yedid Hoshen (CVPR, 2021)

An Image is Worth More Than a Thousand Words: Towards Disentanglement in The Wild. - Aviv Gabbay; Niv Cohen; Yedid Hoshen (NeurIPS, 2021)

The Single-Noun Prior for Image Clustering. - Niv Cohen; Yedid Hoshen (CoRR, 2021)

Out-of-Distribution Detection Without Class Labels. - Niv Cohen; Ron Abutbul; Yedid Hoshen (ECCV Workshops (2), 2022)

"This Is My Unicorn, Fluffy": Personalizing Frozen Vision-Language Representations. - Niv Cohen; Rinon Gal; Eli A. Meirom; Gal Chechik; Yuval Atzmon (ECCV (20), 2022)

Anomaly Detection Requires Better Representations. - Tal Reiss; Niv Cohen; Eliahu Horwitz; Ron Abutbul; Yedid Hoshen (ECCV Workshops (4), 2022)

Approaches Toward Physical and General Video Anomaly Detection. - Laura Kart; Niv Cohen (ICASSP, 2022)

Red PANDA: Disambiguating Anomaly Detection by Removing Nuisance Factors. - Niv Cohen; Jonathan Kahana; Yedid Hoshen (CoRR, 2022)

Improving Zero-Shot Models with Label Distribution Priors. - Jonathan Kahana; Niv Cohen; Yedid Hoshen (CoRR, 2022)

Red PANDA: Disambiguating Image Anomaly Detection by Removing Nuisance Factors. - Niv Cohen; Jonathan Kahana; Yedid Hoshen (ICLR, 2023)

Set Features for Fine-grained Anomaly Detection. - Niv Cohen; Issar Tzachor; Yedid Hoshen (CoRR, 2023)

No Free Lunch: The Hazards of Over-Expressive Representations in Anomaly Detection. - Tal Reiss; Niv Cohen; Yedid Hoshen (CoRR, 2023)

Scaling TabPFN: Sketching and Feature Selection for Tabular Prior-Data Fitted Networks. - Benjamin Feuer; Chinmay Hegde; Niv Cohen (CoRR, 2023)

Circumventing Concept Erasure Methods For Text-To-Image Generative Models. - Minh Pham 005; Kelly O. Marshall; Niv Cohen; Govind Mittal; Chinmay Hegde (ICLR, 2024)

Dataset and Lessons Learned from the 2024 SaTML LLM Capture-the-Flag Competition. - Edoardo Debenedetti; Javier Rando; Daniel Paleka; Silaghi Fineas Florin; Dragos Albastroiu; Niv Cohen; Yuval Lemberg; Reshmi Ghosh; Rui Wen 002; Ahmed Salem 001; Giovanni Cherubin; Santiago Zanella-Béguelin; et al. (NeurIPS, 2024)

TuneTables: Context Optimization for Scalable Prior-Data Fitted Networks. - Benjamin Feuer; Robin Schirrmeister; Valeriia Cherepanova; Chinmay Hegde; Frank Hutter; Micah Goldblum; Niv Cohen; Colin White (NeurIPS, 2024)

SELECT: A Large-Scale Benchmark of Data Curation Strategies for Image Classification. - Benjamin Feuer; Jiawei Xu; Niv Cohen; Patrick Yubeaton; Govind Mittal; Chinmay Hegde (NeurIPS, 2024)

Classifying Nodes in Graphs without GNNs. - Daniel Winter; Niv Cohen; Yedid Hoshen (CoRR, 2024)

Robust Concept Erasure Using Task Vectors. - Minh Pham 005; Kelly O. Marshall; Chinmay Hegde; Niv Cohen (CoRR, 2024)

Set Features for Anomaly Detection. - Niv Cohen; Issar Tzachor; Yedid Hoshen (Trans. Mach. Learn. Res., 2024)

Towards efficient image-based representation of tabular data. - Amit Damri; Mark Last; Niv Cohen (Neural Comput. Appl., 2024)

Deep Unfolding of Full Waveform Inversion for Quantitative Ultrasound Imaging. - Niv Cohen; Yhonatan Kvich; Rui Guo; Yonina C. Eldar (ICASSP, 2025)

Hidden in the Noise: Two-Stage Robust Watermarking for Images. - Kasra Arabi; Benjamin Feuer; R. Teal Witter; Chinmay Hegde; Niv Cohen (ICLR, 2025)

SolidMark: Evaluating Image Memorization in Generative Models. - Nicky Kriplani; Minh Pham 005; Gowthami Somepalli; Chinmay Hegde; Niv Cohen (CoRR, 2025)

SEAL: Semantic Aware Image Watermarking. - Kasra Arabi; R. Teal Witter; Chinmay Hegde; Niv Cohen (CoRR, 2025)

Forging and Removing Latent-Noise Diffusion Watermarks Using a Single Image. - Anubhav Jain 002; Yuya Kobayashi; Naoki Murata; Yuhta Takida; Takashi Shibuya 001; Yuki Mitsufuji; Niv Cohen; Nasir D. Memon; Julian Togelius (CoRR, 2025)

When Are Concepts Erased From Diffusion Models? - Kevin Lu; Nicky Kriplani; Rohit Gandikota; Minh Pham 005; David Bau; Chinmay Hegde; Niv Cohen (CoRR, 2025)