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Is tokenization needed for masked particle modeling?, Leigh, M., Klein, S., Charton, F., Golling, T., Heinrich, L., Kagan, M., Ochoa, I. & Osadchy, M., 30 Jun 2025, In: Machine Learning: Science and Technology. 6, 2, 025075.
Resolving Molecular Perturbations Near Undercoordinated Metals, Poppe, A., Lohia, I., Osadchy, M., Gibson, S. & de Nijs, B., 3 Jun 2025, In: ACS Nano. 19, 21, p. 20120-20127 8 p.
Reconstructing Protected Biometric Templates from Binary Authentication Results, Rahimi, E., Osadchy, M. & Dunkelman, O., 2025, 2025 IEEE International Joint Conference on Biometrics, IJCB 2025. Institute of Electrical and Electronics Engineers Inc., (2025 IEEE International Joint Conference on Biometrics, IJCB 2025).
Vibrational Spectroscopy Can Be Vulnerable to Adversarial Attacks, Liu, J., Osadchy, M., Wang, Y., Wu, Y., Li, E., Hu, X. & Fang, Y., 22 Oct 2024, In: Analytical Chemistry. 96, 42, p. 16570-16580 11 p.
Masked particle modeling on sets: towards self-supervised high energy physics foundation models, Golling, T., Heinrich, L., Kagan, M., Klein, S., Leigh, M., Osadchy, M. & Andrew Raine, J., 1 Sep 2024, In: Machine Learning: Science and Technology. 5, 3, 035074.
Reconstructing Randomly Masked Spectra Helps DNNs Identify Discriminant Wavenumbers, Wu, Y., Liu, J., Wang, Y., Gibson, S., Osadchy, M. & Fang, Y., 1 May 2024, In: IEEE Transactions on Pattern Analysis and Machine Intelligence. 46, 5, p. 3845-3861 17 p., 10375128.
A Unified Approach to Coreset Learning, Maalouf, A., Eini, G., Mussay, B., Feldman, D. & Osadchy, M., 1 May 2024, In: IEEE Transactions on Neural Networks and Learning Systems. 35, 5, p. 6893-6905 13 p.
Mind the Gap: Learning Modality-Agnostic Representations with a Cross-Modality UNet, Niu, X., Li, E., Liu, J., Wang, Y., Osadchy, M. & Fang, Y., 2024, In: IEEE Transactions on Image Processing. 33, p. 655-670 16 p.
Correction to "Mapping Atomic-Scale Metal-Molecule Interactions: Salient Feature Extraction through Autoencoding of Vibrational Spectroscopy Data", Poppe, A., Griffiths, J., Hu, S., Baumberg, J. J., Osadchy, M., Gibson, S. & de Nijs, B., 2 Nov 2023, In: Journal of Physical Chemistry Letters. 14, 43, p. 9793 1 p.
Mapping Atomic-Scale Metal-Molecule Interactions: Salient Feature Extraction through Autoencoding of Vibrational Spectroscopy Data, Poppe, A., Griffiths, J., Hu, S., Baumberg, J. J., Osadchy, M., Gibson, S. & de Nijs, B., 31 Aug 2023, In: Journal of Physical Chemistry Letters. 14, 34, p. 7603-7610 8 p.
A Fast and Reliable Solution to PnP, Using Polynomial Homogeneity and a Theorem of Hilbert, Keren, D., Osadchy, M. & Shahar, A., Jun 2023, In: Sensors. 23, 12, 5585.
Data-Independent Structured Pruning of Neural Networks via Coresets, Mussay, B., Feldman, D., Zhou, S., Braverman, V. & Osadchy, M., Dec 2022, In: IEEE Transactions on Neural Networks and Learning Systems. 33, 12, p. 7829-7841 13 p.
Using deep learning to predict human decisions and using cognitive models to explain deep learning models, Fintz, M., Osadchy, M. & Hertz, U., Dec 2022, In: Scientific Reports. 12, 1, 4736.
How Deep Learning Tools Can Help Protein Engineers Find Good Sequences, Osadchy, M. & Kolodny, R., 24 Jun 2021, In: Journal of Physical Chemistry B. 125, 24, p. 6440-6450 11 p.
Inverting Binarizations of Facial Templates Produced by Deep Learning (and Its Implications), Keller, D., Osadchy, M. & Dunkelman, O., 2021, In: IEEE Transactions on Information Forensics and Security. 16, p. 4184-4196 13 p., 9508363.
Fuzzy Commitments Offer Insufficient Protection to Biometric Templates Produced by Deep Learning, Keller, D., Osadchy, M. & Dunkelman, O., 24 Dec 2020, In: IEEE Transactions on Information Forensics and Security.
LSHR-Net: A hardware-friendly solution for high-resolution computational imaging using a mixed-weights neural network, Bai, F., Liu, J., Liu, X., Osadchy, M., Wang, C. & Gibson, S. J., 17 Sep 2020, In: Neurocomputing. 406, p. 169-181 13 p.
DATA-INDEPENDENT NEURAL PRUNING VIA CORESETS, Mussay, B., Osadchy, M., Braverman, V., Zhou, S. & Feldman, D., 2020.
Data-Independent Structured Pruning of Neural Networks via Coresets, Mussay, B., Feldman, D., Zhou, S., Braverman, V. & Osadchy, M., 2020, 8th International Conference on Learning Representations, ICLR 2020. 24 p.
It is All in the System’s Parameters: Privacy and Security Issues in Transforming Biometric Raw Data into Binary Strings, Osadchy, M. & Dunkelman, O., 1 Sep 2019, In: IEEE Transactions on Dependable and Secure Computing. 16, 5, p. 796-804 9 p.
Dynamic spectrum matching with one-shot learning, Liu, J., Gibson, S. J., Mills, J. & Osadchy, M., 15 Jan 2019, In: Chemometrics and Intelligent Laboratory Systems. 184, p. 175-181 7 p.
LDA classifier monitoring in distributed streaming systems, Bernstein, R., Osadchy, M., Keren, D. & Schuster, A., Jan 2019, In: Journal of Parallel and Distributed Computing. 123, p. 156-167 12 p.
Hinge-minimax learner for the ensemble of hyperplanes, Raviv, D., Hazan, T. & Osadchy, M., 1 Oct 2018, In: Journal of Machine Learning Research. 19, p. 1-30 30 p.
Learning to Support: Exploiting Structure Information in Support Sets for One-Shot Learning, Liu, J., Gibson, S. J. & Osadchy, M., 22 Aug 2018.
Rank and rate: multi-task learning for recommender systems, Hadash, G., Shalom, O. S. & Osadchy, R., 2018, Proceedings of the 12th ACM Conference on Recommender Systems. Publ by ACM, p. 451-454 4 p. (RecSys 2018 - 12th ACM Conference on Recommender Systems).
Deep convolutional neural networks for Raman spectrum recognition: A unified solution, Liu, J., Osadchy, M., Ashton, L., Foster, M., Solomon, C. J. & Gibson, S. J., 7 Nov 2017, In: Analyst. 142, 21, p. 4067-4074 8 p.
No Bot Expects the DeepCAPTCHA! Introducing Immutable Adversarial Examples, with Applications to CAPTCHA Generation, Osadchy, M., Hernandez-Castro, J., Gibson, S., Dunkelman, O. & Perez-Cabo, D., Nov 2017, In: IEEE Transactions on Information Forensics and Security. 12, 11, p. 2640-2653 14 p., 7954632.
Genface: Improving cyber security using realistic synthetic face generation, Osadchy, M., Wang, Y., Dunkelman, O., Gibson, S., Hernandez-Castro, J. & Solomon, C., 2017, Cyber Security Cryptography and Machine Learning - 1st International Conference, CSCML 2017, Proceedings. Dolev, S. & Lodha, S. (eds.). Springer Verlag, p. 19-33 15 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 10332 LNCS).
HoneyFaces: Increasing the Security and Privacy of Authentication Using Synthetic Facial Images, Ohana, M., Dunkelman, O., Gibson, S. & Osadchy, M., 11 Nov 2016.
K-hyperplane hinge-minimax classifier, Osadchy, M., Hazan, T. & Keren, D., 2015, 32nd International Conference on Machine Learning, ICML 2015. Blei, D. & Bach, F. (eds.). International Machine Learning Society (IMLS), p. 1558-1566 9 p. (32nd International Conference on Machine Learning, ICML 2015; vol. 2).
Recognition using specular highlights, Netz, A. & Osadchy, M., 2013, In: IEEE Transactions on Pattern Analysis and Machine Intelligence. 35, 3, p. 639-652 14 p., 6212513.
Poster: Secure authentication from facial attributes with no privacy loss, Dunkelman, O., Osadchy, M. & Sharif, M., 2013, CCS 2013 - Proceedings of the 2013 ACM SIGSAC Conference on Computer and Communications Security. p. 1403-1405 3 p. (Proceedings of the ACM Conference on Computer and Communications Security).
Hybrid classifiers for object classification with a rich background, Osadchy, M., Keren, D. & Fadida-Specktor, B., 2012, Computer Vision, ECCV 2012 - 12th European Conference on Computer Vision, Proceedings. PART 5 ed. p. 284-297 14 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 7576 LNCS, no. PART 5).
Maps of protein structure space reveal a fundamental relationship between protein structure and function, Osadchy, M. & Kolodny, R., 26 Jul 2011, In: Proceedings of the National Academy of Sciences of the United States of America. 108, 30, p. 12301-12306 6 p.
Using specular highlights as pose invariant features for 2D-3D pose estimation, Netz, A. & Osadchy, M., 2011, 2011 IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2011. IEEE Computer Society, p. 721-728 8 p. 5995673. (Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition).
Illumination invariant representation for privacy preserving face identification, Moskovich, B. & Osadchy, M., 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Workshops, CVPRW 2010. IEEE Computer Society, p. 154-161 8 p. 5544620. (2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Workshops, CVPRW 2010).
Using specularities in comparing 3D models and 2D images, Osadchy, M., Jacobs, D., Ramamoorthi, R. & Tucker, D., Sep 2008, In: Computer Vision and Image Understanding. 111, 3, p. 275-294 20 p.
Synergistic face detection and pose estimation with energy-based models, Osadchy, M., Le Cun, Y. & Miller, M. L., May 2007, In: Journal of Machine Learning Research. 8, p. 1197-1215 19 p.
Surface dependent representations for illumination insensitive image comparison, Osadchy, M., Jacobs, D. W. & Lindenbaum, M., Jan 2007, In: IEEE Transactions on Pattern Analysis and Machine Intelligence. 29, 1, p. 98-111 14 p.
Synergistic Face Detection and Pose Estimation with Energy-Based Models, Osadchy, M., Le Cun, Y. & Miller, M. L., 2006, Toward Category-Level Object Recognition. Ponce, J., Hebert, M., Schmid, C. & Zisserman, A. (eds.). Berlin, Heidelberg: Springer Berlin Heidelberg, p. 196-206 11 p. (Lecture Notes in Computer Science; vol. 4170).
Incorporating the Boltzmann prior in object detection using SVM, Osadchy, M. & Keren, D., 2006, Proceedings - 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2006. p. 2095-2101 7 p. 1641010. (Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition; vol. 2).
Synergistic face detection and pose estimation with energy-based models, Osadchy, M., Miller, M. L. & Le Cun, Y., 2005, Advances in Neural Information Processing Systems 17 - Proceedings of the 2004 Conference, NIPS 2004. Neural information processing systems foundation, (Advances in Neural Information Processing Systems).
On the equivalence of common approaches to lighting insensitive recognition, Osadchy, M., Jacobs, D. W. & Lindenbaum, M., 2005, Proceedings - 10th IEEE International Conference on Computer Vision, ICCV 2005. p. 1721-1726 6 p. 1544924. (Proceedings of the IEEE International Conference on Computer Vision; vol. II).
Efficient detection under varying illumination conditions and image plane rotations, Osadchy, M. & Keren, D., Mar 2004, In: Computer Vision and Image Understanding. 93, 3, p. 245-259 15 p.
Whitening for photometric comparison of smooth surfaces under varying illumination, Osadchy, M., Lindenbaum, M. & Jacobs, D., 2004, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Pajdla, T. & Matas, J. (eds.). Springer Verlag, p. 217-228 12 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 3024).
Using specularities for recognition, Osadchy, M., Jacobs, D. & Ramamoorthi, R., 2003, In: Proceedings of the IEEE International Conference on Computer Vision. 2, p. 1512-1519 8 p.
Antifaces: A novel, fast method for image detection, Keren, D., Osadchy, M. & Gotsman, C., Jul 2001, In: IEEE Transactions on Pattern Analysis and Machine Intelligence. 23, 7, p. 747-762 16 p.
Anti-sequences: Event detection by frame stacking, Osadchy, M., Keren, D. & Gal, Y., 2001, In: Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition. 2, p. II46-II51
Image detection under varying illumination and pose, Osadchy, M. & Keren, D., 2001, p. 668-673. 6 p.
Restoring subsampled color images, Keren, D. & Osadchy, M., 1998, In: Machine Vision and Applications. 11, 4, p. 197-202 6 p.

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