N. Intrator

N. Intrator, Y. Shimshoni, 1996, Proceedings of International Workshop on Neural Networks for Identification, Control, Robotics and Signal/Image Processing.

Title: Robust Statistics from Multiple Pings Improves Noise Tolerance in Sonar

L. Cooper, N. Intrator, N. Neretti, 2003 .

Single-Channel EEG Features Reveal an Association With Cognitive Decline in Seniors Performing Auditory Cognitive Assessment

N. Intrator, N. Maimon, L. Molcho, 2022, Frontiers in Aging Neuroscience.

Face recognition using a hybrid supervised/unsupervised neural network

D. Reisfeld, Y. Yeshurun, N. Intrator, 1994, ICPR.

Volitional limbic neuromodulation has a multifaceted clinical benefit in Fibromyalgia patients

N. Intrator, T. Hendler, M. Cavazza, 2018 .

Learning low-dimensional representations via the usage of multiple-class labels

S. Edelman, N. Intrator, 1997 .

Competitive Learning

N. Intrator, 1998, Encyclopedia of Machine Learning and Data Mining.

Face recognition using a hybrid supervised/unsupervised neural network

D. Reisfeld, Y. Yeshurun, N. Intrator, 1996, Proceedings of the 12th IAPR International Conference on Pattern Recognition, Vol. 3 - Conference C: Signal Processing (Cat. No.94CH3440-5).

Feature Extraction Using an Unsupervised Technical Neural Network

N. Intrator, 2022 .

A novel cardiotoxic polypeptide from the venom of Atractaspis engaddensis (burrowing asp): cardiac effects in mice and isolated rat and human heart preparations.

N. Intrator, Y. Oron, S. Gitter, 1988, Toxicon : official journal of the International Society on Toxinology.

A description of the MEDIA study: A Method for Evaluating Digital endpoints In Alzheimer's disease (Preprint)

N. Intrator, J. Praestgaard, Jessica Robin, 2021, JMIR Research Protocols.

1 Motion Compensation Improves Medical Ultrasound Image Quality

L. Cooper, N. Intrator, N. Neretti, 2006 .

Face recognition using a hybrid supervised/unsupervised neural network

Nathan Intrator, Yehezkel Yeshurun, Daniel Reisfeld, 1994, Proceedings of the 12th IAPR International Conference on Pattern Recognition, Vol. 3 - Conference C: Signal Processing (Cat. No.94CH3440-5).

Effect of Binocular Cortical Misalignment on Ocular Dominance and Orientation Selectivity

Nathan Intrator, Leon N. Cooper, Harel Z. Shouval, 1996, Neural Computation.

MAP fusion method for superresolution of images with locally varying pixel quality

Nicola Neretti, Nathan Intrator, Kio Kim, 2008, Int. J. Imaging Syst. Technol..

Ensemble-based Feature Selection Criteria

Nathan Intrator, Terry Windeatt, Matthew Prior, 2007, MLDM Posters.

Blurred face recognition via a hybrid network architecture

Nathan Intrator, Inna Stainvas, N. Intrator, 2000, Proceedings 15th International Conference on Pattern Recognition. ICPR-2000.

Receptive Field Formation in Natural Scene Environments: Comparison of Single-Cell Learning Rules

Nathan Intrator, Leon N. Cooper, Brian S. Blais, 1997, Neural Computation.

Theory of Cortical Plasticity

Nathan Intrator, Leon N. Cooper, Brian S. Blais, 2004 .

The use of pneumoperitoneum during laparoscopic surgery as a model to study pathophysiologic phenomena: the correlation of cardiac functionality with computerized acoustic indices--preliminary data.

N. Intrator, A. Bickel, A. Eitan, 2012, Journal of laparoendoscopic & advanced surgical techniques. Part A.

Respiratory modulation of heart sound morphology.

Nathan Intrator, Noam Gavriely, Guy Amit, 2009, American journal of physiology. Heart and circulatory physiology.

Cluster analysis and classification of heart sounds

Nathan Intrator, Noam Gavriely, Guy Amit, 2009, Biomed. Signal Process. Control..

Information theory and visual plasticity

Nathan Intrator, Leon N. Cooper, L. Cooper, 1998 .

Learning as Extraction of Low-Dimensional Representations

Nathan Intrator, Shimon Edelman, S. Edelman, 1997 .

Systems biology and brain activity in neuronal pathways by smart device and advanced signal processing

Nathan Intrator, Gastone Castellani, Daniel Remondini, 2014, Front. Genet..

Targeting c-Myc-activated genes with a correlation method: detection of global changes in large gene expression network dynamics.

D Remondini, N Intrator, N. Intrator, 2005, Proceedings of the National Academy of Sciences of the United States of America.

Connectivity maps based analysis of EEG for the advanced diagnosis of schizophrenia attributes

Nathan Intrator, Abraham Peled, Noa Fogelson, 2017, PloS one.

Using unsupervised incremental learning to cope with gradual concept drift

Nathan Intrator, Galit Yovel, David Hadas, 2011, Connect. Sci..

Bootstrapping with Noise: An Effective Regularization Technique

Nathan Intrator, Yuval Raviv, N. Intrator, 1996, Connect. Sci..

Reduced neural activity during volatile anesthesia compared to TIVA: evidence from a novel EEG signal processing analysis through a randomized controlled trial

N. Intrator, N. Maimon, L. Molcho, 2020, 2009.14264.

Neuronal Fiber Delineation in Area of Edema from Diffusion Weighted MRI

Nathan Intrator, Ofer Pasternak, Yaniv Assaf, 2005, NIPS.

Computational models of perceptual learning

S. Edelman, N. Intrator, 2021 .

Mosaicing of acoustic camera images

Nicola Neretti, Nathan Intrator, Kio Kim, 2005 .

Acoustic camera image mosaicing and super-resolution

N. Neretti, N. Intrator, K. Kim, 2004, Oceans '04 MTS/IEEE Techno-Ocean '04 (IEEE Cat. No.04CH37600).

Identification of a T cell gene expression clock obtained by exploiting a MZ twin design

N. Intrator, G. Castellani, C. Franceschi, 2017, Scientific Reports.

Multimodality exploration by an unsupervised projection pursuit neural network

Nathan Intrator, Yocheved Dotan, N. Intrator, 1998, IEEE Trans. Neural Networks.

Multi-Dimensional Feature Scoring For Gene Expression Data

Nathan Intrator, Niv Efron, N. Intrator, 2006 .

Volitional limbic neuromodulation exerts a beneficial clinical effect on Fibromyalgia

Marc Cavazza, Fred Charles, Nathan Intrator, 2019, NeuroImage.

Boosted Mixture of Experts: An Ensemble Learning Scheme

Nathan Intrator, Ran Avnimelech, N. Intrator, 1999, Neural Computation.

Inference of Brain Mental States from Spatio-temporal Analysis of EEG Single Trials

Nathan Intrator, Talma Hendler, Andrey Zhdanov, 2011, BIOSIGNALS.

Making a Low-dimensional Representation Suitable for Diverse Tasks

Nathan Intrator, N. Intrator, 1996, Connect. Sci..

Monitoring Cardiac Stress Using Features Extracted From S1 Heart Sounds

Nathan Intrator, Jonathan Herzig, Amitai Bickel, 2015, IEEE Transactions on Biomedical Engineering.

Striking of underwater prey by a reef heron,Egretta gularis schistacea

Gadi Katzir, Nathan Intrator, N. Intrator, 1987, Journal of Comparative Physiology.

Neural dynamics necessary and sufficient for transition into pre-sleep induced by EEG NeuroFeedback

Nathan Intrator, Talma Hendler, Ilana Podlipsky, 2014, NeuroImage.

Categorized EEG Neurofeedback Performance Unveils Simultaneous fMRI Deep Brain Activation

Nathan Intrator, Talma Hendler, Ilana Podlipsky, 2011, MLINI.

Probabilistic principles in unsupervised learning of visual structure: human data and a model

Nathan Intrator, Shimon Edelman, Hwajin Yang, 2001, NIPS.

Abstracts of the 16th Annual Meeting of The Israel Society for Neuroscience Eilat, Israel, November 25–27, 2007

Yonina C. Eldar, Karl J. Friston, Leslie G. Ungerleider, 2008, Neural plasticity.

Discovery of multiple level heart-sound morphological variability resulting from changes in physiological states

Nathan Intrator, Noam Gavriely, Svetlana Kofman, 2012, Biomed. Signal Process. Control..

Detection and identification of heart sounds using homomorphic envelogram and self-organizing probabilistic model

N. Intrator, D. Gill, N. Gavrieli, 2005, Computers in Cardiology, 2005.

On the Use of Projection Pursuit Constraints for Training Neural Networks

Nathan Intrator, N. Intrator, 1992, NIPS.

Stationary underwater prey missed by reef herons,Egretta gularis: head position and light refraction at the moment of strike

N. Intrator, G. Katzir, A. Lotem, 1989, Journal of Comparative Physiology A.

Robust Interpretation of Neural-Network Models

Nathan Intrator, Orna Intrator, N. Intrator, 1997 .

Using Iterative Ridge Regression to Explore Associations Between Conditioned Variables

Nathan Intrator, Nimrod Bar-Yaakov, Zehava Grossman, 2012, J. Comput. Biol..

Continuous Monitoring of Mental Load During Virtual Simulator Training for Laparoscopic Surgery Reflects Laparoscopic Dexterity: A Comparative Study Using a Novel Wireless Device

N. Intrator, N. Maimon, L. Molcho, 2022, Frontiers in Neuroscience.

Classification of underwater mammals using feature extraction based on time-frequency analysis and BCM theory

Nathan Intrator, Leon N. Cooper, Harel Z. Shouval, 1998, IEEE Trans. Signal Process..

Postural control in karate practitioners: Does practice make perfect?

N. Intrator, J. Hausdorff, N. Maimon, 2020, Gait & posture.

Machine learning fMRI classifier delineates subgroups of schizophrenia patients

Nathan Intrator, Talma Hendler, Shahar Jamshy, 2014, Schizophrenia Research.

Offline cursive script word recognition – a survey

Ehud Rivlin, Nathan Intrator, Tal Steinherz, 1999, International Journal on Document Analysis and Recognition.

A Productive, Systematic Framework for the Representation of Visual Structure

Nathan Intrator, Shimon Edelman, S. Edelman, 2000, NIPS.

(coarse Coding of Shape Fragments) (retinotopy) Representation of Structure

Nathan Intrator, Shimon Edelman, S. Edelman, 2000 .

Optimal ensemble averaging of neural networks

Nathan Intrator, Ury Naftaly, David Horn, 1997 .

The dark side of the alpha rhythm: fMRI evidence for induced alpha modulation during complete darkness

Dean Cvetkovic, Nathan Intrator, Talma Hendler, 2013, The European journal of neuroscience.

Solutions of the BCM learning rule in a network of lateral interacting nonlinear neurons.

L N Cooper, N Intrator, L. Cooper, 1999, Network.

Detection of Cognitive Decline using a Single-Channel EEG with an Interactive Assessment Tool

N. Intrator, N. Maimon, L. Molcho, 2021 .

Robust modeling based on optimized EEG bands for functional brain state inference

Nathan Intrator, Talma Hendler, Ilana Podlipsky, 2012, Journal of Neuroscience Methods.

Limbic Activity Modulation Guided by Functional Magnetic Resonance Imaging–Inspired Electroencephalography Improves Implicit Emotion Regulation

Nathan Intrator, Talma Hendler, Avihay Cohen, 2016, Biological Psychiatry.

The Effect of Noise on a Class of Energy-Based Learning Rules

N. Intrator, A. Bazzani, D. Remondini, 2003, Neural Computation.

Unsupervised Learning of Visual Structure

Nathan Intrator, Shimon Edelman, Judah S. Jacobson, 2002, Biologically Motivated Computer Vision.

One-Class FMRI-Inspired EEG Model for Self-Regulation Training

Talma Hendler, Nathan Intrator, Avihay Cohen, 2016, PloS one.

Classification of seismic signals by integrating ensembles of neural networks

Nathan Intrator, Yair Shimshoni, N. Intrator, 1998, IEEE Trans. Signal Process..

Abstracts of the 16th Annual Meeting of The Israel Society for Neuroscience Eilat, Israel, November 25–27, 2007

Yonina C. Eldar, Karl J. Friston, Leslie G. Ungerleider, 2008, Neural plasticity.

Early perceptual loss in depression

Yonina C. Eldar, Karl J. Friston, Charles R. Seger, 2007 .

Schizophrenia Detection and Classification by Advanced Analysis of EEG Recordings Using a Single Electrode Approach

Nathan Intrator, Noa Fogelson, Avi Peled, 2015, PloS one.

An EEG Finger-Print of fMRI deep regional activation

Nathan Intrator, Talma Hendler, Ilana Podlipsky, 2014, NeuroImage.

Ensemble of hybrid networks with strong regularization

Nathan Intrator, Shimon Cohen, N. Intrator, 2003, The European Symposium on Artificial Neural Networks.

Unsupervised Learning of Visual Structure

Nathan Intrator, Shimon Edelman, Judah S. Jacobson, 2002, Biologically Motivated Computer Vision.

Visual Processing of Object Structure

Nathan Intrator, Shimon Edelman, S. Edelman, 2002 .

A Real-Time Kinect Signature-Based Patient Home Monitoring System

Nathan Intrator, Meir Plotnik, Gaddi Blumrosen, 2016, Sensors.

A Hybrid Projection-based and Radial Basis Function Architecture: Initial Values and Global Optimisation

N. Intrator, Shimon Cohen, 2002, Pattern Analysis and Applications.

A Hybrid Projection Based and Radial Basis Function Architecture

Nathan Intrator, Shimon Cohen, N. Intrator, 2000, Multiple Classifier Systems.

A hybrid projection based and radial basis function architecture : Initial values and global optimization ∗

N. Intrator, Shimon Cohen, 2000 .

An integrated approach to the study of object features in visual recognition

Heinrich H. Bülthoff, Nathan Intrator, Shimon Edelman, 1995 .

On Different Model Selection Criteria In A Forward And Backward Regression Hybrid Network

Nathan Intrator, Shimon Cohen, N. Intrator, 2004, Int. J. Pattern Recognit. Artif. Intell..

A Study of Ensemble of Hybrid Networks with Strong Regularization

Nathan Intrator, Shimon Cohen, N. Intrator, 2003, Multiple Classifier Systems.

Global Optimization of RBF Networks

Nathan Intrator, Shimon Cohen, N. Intrator, 2000 .

Forward and Backward Selection in Regression Hybrid Network

Nathan Intrator, Shimon Cohen, N. Intrator, 2002, Multiple Classifier Systems.

Towards a real time kinect signature based human activity assessment at home

Nathan Intrator, Meir Plotnik, Gaddi Blumrosen, 2015, 2015 IEEE 12th International Conference on Wearable and Implantable Body Sensor Networks (BSN).

Large Ensemble Averaging

Nathan Intrator, David Horn, Ury Naftaly, 1996, Neural Networks.

Fundamentals of Artificial Neural Networks

M.H. Hassoun, N. Intrator, M. Hassoun, 1996, Proceedings of the IEEE.

Theory of Cortical Plasticity: (With Software Package “PLASTICITY”)

Nathan Intrator, Nathan Intrator, Leon N. Cooper, 2004 .

Optimal spontaneous activity in neural network modeling

Nathan Intrator, Gastone C. Castellani, Leon N. Cooper, 2002, Neurocomputing.

A Robust and Efficient Spatio-Temporal Feature Selection for Interpretation of EEG Single Trials

Nathan Intrator, Talma Hendler, Andrey Zhdanov, 2011, BIOSTEC.

3D Object Recognition Using Unsupervised Feature Extraction

Heinrich H. Bülthoff, Nathan Intrator, Shimon Edelman, 1991, NIPS.

Three-Dimensional Object Recognition Using an Unsupervised BCM Network The Usefulness of Distinguishing Features

N. Intrator, Joshua I. Gold, 2011 .

Boosting Regression Estimators

Nathan Intrator, Ran Avnimelech, N. Intrator, 1999, Neural Computation.

Face detection by direct convexity estimation

Nathan Intrator, Yehezkel Yeshurun, Ariel Tankus, 1997, Pattern Recognit. Lett..

Volitional limbic neuromodulation has a multifaceted clinical benefit in Fibromyalgia patients

N. Intrator, T. Hendler, M. Cavazza, 2018 .

Machine Learning Framework for Inferring Cognitive State from Magnetoencephalographic (MEG) Signals

Nathan Intrator, Talma Hendler, Leslie G. Ungerleider, 2008 .

Rapid Object Category Adaptation during Unlabelled Classification

Nathan Intrator, Galit Yovel, David Hadas, 2010, Perception.

Conservation of total T-cell counts during HIV infection: alternative hypotheses and implications.

N. Intrator, Z. Grossman, R. Herberman, 1998, Journal of acquired immune deficiency syndromes and human retrovirology : official publication of the International Retrovirology Association.

Inferring Functional Brain States Using Temporal Evolution of Regularized Classifiers

Nathan Intrator, Talma Hendler, Leslie G. Ungerleider, 2007, Comput. Intell. Neurosci..

Evaluation of an auditory model for echo delay accuracy in wideband biosonar.

Nicola Neretti, Nathan Intrator, James A Simmons, 2003, The Journal of the Acoustical Society of America.

Time-frequency model for echo-delay resolution in wideband biosonar.

Nicola Neretti, Nathan Intrator, James A Simmons, 2003, The Journal of the Acoustical Society of America.

Evaluation of Parkinsons disease with early diagnosis using single-channel EEG features and auditory cognitive assessment

N. Intrator, N. Maimon, L. Molcho, 2023, 2308.03406.

Objective function formulation of the BCM theory of visual cortical plasticity: Statistical connections, stability conditions

L. Cooper, N. Intrator, 1992, Neural Networks.