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Raanan Y. Yehezkel Rohekar
Raanan Y. Yehezkel Rohekar
Research Scientist, Intel Labs
Verified email at intel.com
Title
Cited by
Cited by
Year
Bayesian network structure learning by recursive autonomy identification
R Yehezkel, B Lerner
Journal of Machine Learning Research 10 (Jul), 1527-1570, 2009
131*2009
System and method for suspect search
Y Gurwicz, RY Yehezkel, V Goldner, G Boudoukh, G Blumstein-koren, ...
US Patent 9,471,849, 2016
912016
System and method for inferring user intent based on eye movement during observation of a display screen
M Jacob, R Yehezkel
US Patent 9,176,581, 2012
702012
Multiclass object classification for real-time video surveillance systems
Y Gurwicz, R Yehezkel, B Lachover
Pattern Recognition Letters 32 (6), 805-815, 2011
642011
On the fly deep learning in machine learning for autonomous machines
RYY Rohekar
US Patent 10,572,773, 2020
532020
Constructing deep neural networks by Bayesian network structure learning
RY Rohekar, S Nisimov, Y Gurwicz, G Koren, G Novik
Advances in Neural Information Processing Systems (NeurIPS) 2018, 2018
372018
System and method for quick object verification
G Blumstein-koren, RY Yehezkel
US Patent 8,854,474, 2014
292014
System and method for semantic video content analysis
RY Yehezkel, G Blumstein-koren, Y Gurwicz
US Patent 8,743,205, 2014
272014
Iterative Causal Discovery in the Possible Presence of Latent Confounders and Selection Bias
RY Rohekar, S Nisimov, Y Gurwicz, G Novik
Advances in Neural Information Processing Systems (NeurIPS) 2021, 2021
242021
Video indexing with viewer reaction estimation and visual cue detection
R Yehezkel, D Stanhill
US Patent 9,247,225, 2016
242016
Emotion-related query processing
R Rappoport, R Yehezkel, R Fishtein, S Goffman, G Jacob, O Gershon, ...
US Patent 9,594,807, 2017
222017
Systems and methods for self-learning, content-aware affect recognition
R Yehezkel, D Stanhill, E Rond
US Patent App. 14/578,623, 2016
202016
Modeling uncertainty by learning a hierarchy of deep neural connections
RY Rohekar, Y Gurwicz, S Nisimov, G Novik
Advances in Neural Information Processing Systems (NeurIPS) 2019, 2019
19*2019
Bayesian structure learning by recursive bootstrap
RY Rohekar, Y Gurwicz, S Nisimov, G Koren, G Novik
Advances in Neural Information Processing Systems (NeurIPS) 2018, 2018
182018
System and method for learning the structure of deep convolutional neural networks
G Koren, RYY Rohekar, S Nisimov, G Novik
US Patent 11,010,658, 2021
152021
Facilitating dynamic affect-based adaptive representation and reasoning of user behavior on computing devices
RY Yehezkel, D Stanhill
US Patent 20,160,086,088, 2016
152016
Image storage and retrieval based on eye movements
R Yehezkel, M Jacob
US Patent 8,942,514, 2012
122012
From temporal to contemporaneous iterative causal discovery in the presence of latent confounders
RY Rohekar, S Nisimov, Y Gurwicz, G Novik
International Conference on Machine Learning, 39939-39950, 2023
72023
Improving Efficiency and Accuracy of Causal Discovery Using a Hierarchical Wrapper
S Nisimov, Y Gurwicz, RY Rohekar, G Novik
Uncertainty in Artificial Intelligence (UAI) 2021, workshop on Tractable …, 2021
52021
LVLM-Intrepret: An Interpretability Tool for Large Vision-Language Models
GBM Stan, RY Rohekar, Y Gurwicz, ML Olson, A Bhiwandiwalla, E Aflalo, ...
arXiv preprint arXiv:2404.03118, 2024
42024
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