Larry M. Manevitz

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Finite–Element Mesh Generation Using Self–Organizing Neural Networks

Dan Givoli, Malik Yousef, Larry M. Manevitz, 1997 .

Analyzing cognitive processes from complex neuro-physiologically based data: some lessons

Larry M. Manevitz, Alex Frid, L. Manevitz, 2019, Annals of Mathematics and Artificial Intelligence.

Assigning meaning to data: Using sparse distributed memory for multilevel cognitive tasks

Larry M. Manevitz, Yigal Zemach, 1997, Neurocomputing.

Stability and Topology in Reservoir Computing

Hananel Hazan, Larry M. Manevitz, 2010, MICAI.

Combination calculi for uncertainty reasoning: representing uncertainty using distributions

Robert A. Hummel, Larry M. Manevitz, R. Hummel, 1997, Annals of Mathematics and Artificial Intelligence.

Computational Diagnosis of Parkinson's Disease Directly from Natural Speech Using Machine Learning Techniques

Hananel Hazan, Lorraine O. Ramig, Larry M. Manevitz, 2014, 2014 IEEE International Conference on Software Science, Technology and Engineering.

The Liquid State Machine is not Robust to Problems in Its Components but Topological Constraints Can Restore Robustness

Hananel Hazan, Larry M. Manevitz, L. Manevitz, 2016, IJCCI.

Retrieval of Collaborative Filtering Nearest Neighbors in a Content-Addressable Space

Shlomo Berkovsky, Larry M. Manevitz, Yaniv Eytani, 2006, ICEIS.

Kohonen-Based Topological Clustering as an Amplifier for Multi-Class Classification for Parkinson’s Disease

Larry M. Manevitz, Alex Frid, Ohad Mosafi, 2018, 2018 IEEE International Conference on the Science of Electrical Engineering in Israel (ICSEE).

Interactions between Hemispheres When Disambiguating Ambiguous Homograph Words during Silent Reading

Hananel Hazan, Larry M. Manevitz, Zohar Eviatar, 2016, IJCCI.

Classifying the valence of autobiographical memories from fMRI data

Larry M. Manevitz, Alex Frid, Norberto Eiji Nawa, 2020, Annals of Mathematics and Artificial Intelligence.

A web navigation system based on a neural network user-model trained with only positive web documents

Malik Yousef, Larry M. Manevitz, 2004, Web Intell. Agent Syst..

Classifying cognitive states of brain activity via one-class neural networks with feature selection by genetic algorithms

David R. Hardoon, Larry M. Manevitz, Omer Boehm, 2011, Int. J. Mach. Learn. Cybern..

Cognition and Neurocomputation

Larry M. Manevitz, Alex Frid, L. Manevitz, 2020, Ann. Math. Artif. Intell..

Topological constraints and robustness in liquid state machines

Hananel Hazan, Larry M. Manevitz, L. Manevitz, 2012, Expert Syst. Appl..

Interweaving Kohonen Maps of Different Dimensions to Handle Measure Zero Constraints on Topological Mappings

Larry M. Manevitz, L. Manevitz, 1997, Neural Processing Letters.

Towards Classifying Human Phonemes without Encodings via Spatiotemporal Liquid State Machines: Extended Abstract

Hananel Hazan, Larry M. Manevitz, Alex Frid, 2014, 2014 IEEE International Conference on Software Science, Technology and Engineering.

Efficient Collaborative Filtering in Content-Addressable Spaces

Shlomo Berkovsky, Larry M. Manevitz, Yaniv Eytani, 2007, Personalization Techniques and Recommender Systems.

A statistical approach to the representation of uncertainty in beliefs using spread of opinions

Robert A. Hummel, Larry M. Manevitz, 1996, IEEE Trans. Syst. Man Cybern. Part A.

Combining Bodies of Dependent Information

Robert A. Hummel, Larry M. Manevitz, 1987, IJCAI.

Fuzzy Independence and Extended Conditional Probability

Edward K. Wong, Mark E. Hoffman, Larry M. Manevitz, 1996, Inf. Sci..

Learning BOLD Response in fMRI by Reservoir Computing

Hananel Hazan, Diego Sona, Paolo Avesani, 2011, 2011 International Workshop on Pattern Recognition in NeuroImaging.

One-class document classification via Neural Networks

Malik Yousef, Larry M. Manevitz, L. Manevitz, 2007, Neurocomputing.

Triangle 02 Operators and Alternating Sentences in Arithmetic

Larry M. Manevitz, Jonathan Stavi, J. Stavi, 1980, J. Symb. Log..

Non-parametric temporal modeling of the hemodynamic response function via a liquid state machine

Hananel Hazan, Diego Sona, Paolo Avesani, 2015, Neural Networks.

Multi-Class Classification in Parkinson’s Disease by Leveraging Internal Topological Structure of the Data and of the Label Space

Larry M. Manevitz, Alex Frid, Ohad Mosafi, 2019, 2019 International Joint Conference on Neural Networks (IJCNN).

fMRI Analysis via One-class Machine Learning Techniques

David R. Hardoon, Larry M. Manevitz, D. Hardoon, 2005, IJCAI.

Heuristic finite element node numbering

Dan Givoli, Larry M. Manevitz, Micha Margi, 1993 .

Two hemispheres—two networks: a computational model explaining hemispheric asymmetries while reading ambiguous words

Hananel Hazan, Larry M. Manevitz, Zohar Eviatar, 2010, Annals of Mathematics and Artificial Intelligence.

One-Class SVMs for Document Classification

Malik Yousef, Larry M. Manevitz, L. Manevitz, 2002, J. Mach. Learn. Res..

One-class Machine Learning Approach for fMRI Analysis

David R. Hardoon, Larry M. Manevitz, D. Hardoon, 2005 .

Classification and Clustering of Brain Injuries from Motion Data of Patients in a Virtual Reality Environment

Uri Feintuch, Larry M. Manevitz, Natan Silnitsky, 2018, IJCCI.

Windows on the Mind: Some recent aspects of modeling and pattern recognition of cognition

Larry M. Manevitz, L. Manevitz, 2010, ISAIM.

Finite-Element Mesh Adaptation via Time Series Prediction Using Neural Networks

Dan Givoli, Larry M. Manevitz, Akram Bitar, 2002 .

Efficient Collaborative Filtering in Content-Addressable Spaces

Shlomo Berkovsky, Larry M. Manevitz, Yaniv Eytani, 2007, Personalization Techniques and Recommender Systems.

Collaborative Filtering Based on Content Addressing

Shlomo Berkovsky, Larry M. Manevitz, Yaniv Eytani, 2006, ICEIS.

Approximating Functions by Neural Networks: A Constructive Solution in the Uniform Norm

Moshe Shoham, Larry M. Manevitz, Mark Meltser, 1996, Neural Networks.

Differences and Interactions Between Cerebral Hemispheres When Processing Ambiguous Words

Hananel Hazan, Larry M. Manevitz, Zohar Eviatar, 2008, WAPCV.

Towards One-Class Pattern Recognition in Brain Activity via Neural Networks

David R. Hardoon, Larry M. Manevitz, Omer Boehm, 2010, MICAI.

Document classification on neural networks using only positive examples (poster session)

Malik Yousef, Larry M. Manevitz, 2000, SIGIR '00.

The Existence of Two Variant Processes in Human Declarative Memory: Evidence Using Machine Learning Classification Techniques in Retrieval Tasks

Hananel Hazan, Larry M. Manevitz, Alex Frid, 2016, Trans. Comput. Collect. Intell..

The Finite Element Method and Soft Computing

Dan Givoli, Larry M. Manevitz, L. Manevitz, 1999 .

Classification and biomarker identification using gene network modules and support vector machines

Louise C. Showe, Malik Yousef, Larry M. Manevitz, 2009, BMC Bioinformatics.

Classification from generation: Recognizing deep grammatical information during reading from rapid event-related fMRI

Hananel Hazan, Tali Bitan, Larry M. Manevitz, 2016, 2016 International Joint Conference on Neural Networks (IJCNN).

Using Neural Network Models to Model Cerebral Hemispheric Differences in Processing Ambiguous Words

Hananel Hazan, Larry M. Manevitz, Zohar Eviatar, 2007, NeSy.

Diagnosis of Parkinson's disease from continuous speech using deep convolutional networks without manual selection of features

Larry M. Manevitz, Alex Frid, Ariel Kantor, 2016, 2016 IEEE International Conference on the Science of Electrical Engineering (ICSEE).

Temporal Sparse Distributed Memory: Identifying Temporal Patterns via Homeomorphic Contractions of Memory

Larry M. Manevitz, L. Manevitz, 1992 .

Recognizing deep grammatical information during reading from event related fMRI

Hananel Hazan, Tali Bitan, Larry M. Manevitz, 2014, 2014 IEEE 28th Convention of Electrical & Electronics Engineers in Israel (IEEEI).

Implementing a “Sense of Time” via Entropy in Associative Memories

Larry M. Manevitz, L. Manevitz, 1991 .

Machine learning techniques and the existence of variant processes in humans declarative memory

Hananel Hazan, Larry M. Manevitz, Alex Frid, 2015, 2015 7th International Joint Conference on Computational Intelligence (IJCCI).

Features and Machine Learning for Correlating and Classifying between Brain Areas and Dyslexia pdf

Larry M. Manevitz, Alex Frid, L. Manevitz, 2018, ArXiv.

Towards automating the finite element method: a test-bed for soft computing

Dan Givoli, Larry M. Manevitz, L. Manevitz, 2003, Appl. Soft Comput..

Neural network time series forecasting of finite-element mesh adaptation

Dan Givoli, Larry M. Manevitz, Akram Bitar, 2005, Neurocomputing.

A simulation tool for modeling the influence of anatomy on information flow using discrete integrate and fire neurons

Larry M. Manevitz, Maya Maimon, L. Manevitz, 2008, J. Comb. Optim..

Design and Selection of Features under ERP for Correlating and Classifying between Brain Areas and Dyslexia via Machine Learning

Larry M. Manevitz, Alex Frid, L. Manevitz, 2020, 2020 International Joint Conference on Neural Networks (IJCNN).

02 operators and alternating sentences in arithmetic

Larry M. Manevitz, Jonathan Stavi, J. Stavi, 1980 .

Decoding the Formation of New Semantics: MVPA Investigation of Rapid Neocortical Plasticity during Associative Encoding through Fast Mapping

Hananel Hazan, Larry M. Manevitz, Asaf Gilboa, 2015, Neural plasticity.