Niv Cohen
Niv Cohen
Research Scientist at New York University (post-doc)
Verified email at - Homepage
Cited by
Cited by
Sub-image anomaly detection with deep pyramid correspondences
N Cohen, Y Hoshen
arXiv preprint arXiv:2005.02357, 2020
PANDA--Adapting Pretrained Features for Anomaly Detection
T Reiss*, N Cohen*, L Bergman, Y Hoshen
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020
Deep nearest neighbor anomaly detection
L Bergman*, N Cohen*, Y Hoshen
arXiv preprint arXiv:2002.10445, 2020
RNA structural determinants of optimal codons revealed by MAGE-Seq
ED Kelsic, H Chung, N Cohen, J Park, HH Wang, R Kishony
Cell systems 3 (6), 563-571. e6, 2016
“This is my unicorn, Fluffy”: Personalizing frozen vision-language representations
N Cohen, R Gal, EA Meirom, G Chechik, Y Atzmon
European conference on computer vision, 558-577, 2022
An image is worth more than a thousand words: Towards disentanglement in the wild
A Gabbay, N Cohen, Y Hoshen
Advances in Neural Information Processing Systems 34, 9216-9228, 2021
Anomaly detection requires better representations
T Reiss, N Cohen, E Horwitz, R Abutbul, Y Hoshen
European Conference on Computer Vision, 56-68, 2022
Improving zero-shot models with label distribution priors
J Kahana, N Cohen, Y Hoshen
arXiv preprint arXiv:2212.00784, 2022
Set Features for Anomaly Detection
N Cohen, I Tzachor, Y Hoshen
arXiv preprint arXiv:2311.14773, 2023
Chip-scale atomic wave-meter enabled by machine learning
E Edrei, N Cohen, E Gerstel, S Gamzu-Letova, N Mazurski, U Levy
Science advances 8 (15), eabn3391, 2022
Circumventing concept erasure methods for text-to-image generative models
M Pham, KO Marshall, N Cohen, G Mittal, C Hegde
The Twelfth International Conference on Learning Representations, 2023
Out-of-distribution detection without class labels
N Cohen, R Abutbul, Y Hoshen
European Conference on Computer Vision, 101-117, 2022
Red PANDA: Disambiguating image anomaly detection by removing nuisance factors
N Cohen, J Kahana, Y Hoshen
The Eleventh International Conference on Learning Representations, 2022
Scaling TabPFN: Sketching and Feature Selection for Tabular Prior-Data Fitted Networks
B Feuer, C Hegde, N Cohen
arXiv preprint arXiv:2311.10609, 2023
Language-Guided Image Clustering
N Cohen, Y Hoshen
Detecting anomalous proteins using deep representations
T Michael-Pitschaze, N Cohen, D Ofer, Y Hoshen, M Linial
NAR Genomics and Bioinformatics 6 (1), lqae021, 2024
TuneTables: Context Optimization for Scalable Prior-Data Fitted Networks
B Feuer, RT Schirrmeister, V Cherepanova, C Hegde, F Hutter, ...
arXiv preprint arXiv:2402.11137, 2024
Disentanglement of single-cell data with biolord
Z Piran, N Cohen, Y Hoshen, M Nitzan
Nature Biotechnology, 1-6, 2024
No free lunch: The hazards of over-expressive representations in anomaly detection
T Reiss, N Cohen, Y Hoshen
arXiv preprint arXiv:2306.07284, 2023
Robust Concept Erasure Using Task Vectors
M Pham, KO Marshall, C Hegde, N Cohen
arXiv preprint arXiv:2404.03631, 2024
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