Hananel Hazan
Hananel Hazan
Allen Discovery Center, Tufts University, USA
Verified email at hazan.org.il - Homepage
Title
Cited by
Cited by
Year
Decoding the formation of new semantics: MVPA investigation of rapid neocortical plasticity during associative encoding through fast mapping
T Atir-Sharon, A Gilboa, H Hazan, E Koilis, LM Manevitz
Neural plasticity 2015, 2015
472015
Bindsnet: A machine learning-oriented spiking neural networks library in python
H Hazan, DJ Saunders, H Khan, D Patel, DT Sanghavi, HT Siegelmann, ...
Frontiers in neuroinformatics 12, 89, 2018
402018
Early diagnosis of Parkinson's disease via machine learning on speech data
H Hazan, D Hilu, L Manevitz, LO Ramig, S Sapir
2012 IEEE 27th Convention of Electrical and Electronics Engineers in Israel, 1-4, 2012
322012
Unsupervised learning with self-organizing spiking neural networks
H Hazan, D Saunders, DT Sanghavi, H Siegelmann, R Kozma
2018 International Joint Conference on Neural Networks (IJCNN), 1-6, 2018
312018
Computational diagnosis of Parkinson's Disease directly from natural speech using machine learning techniques
A Frid, EJ Safra, H Hazan, LL Lokey, D Hilu, L Manevitz, LO Ramig, ...
2014 IEEE International Conference on Software Science, Technology and …, 2014
262014
Topological constraints and robustness in liquid state machines
H Hazan, LM Manevitz
Expert Systems with Applications 39 (2), 1597-1606, 2012
252012
Locally connected spiking neural networks for unsupervised feature learning
DJ Saunders, D Patel, H Hazan, HT Siegelmann, R Kozma
Neural Networks 119, 332-340, 2019
112019
Stability and topology in reservoir computing
L Manevitz, H Hazan
Mexican International Conference on Artificial Intelligence, 245-256, 2010
112010
Improved robustness of reinforcement learning policies upon conversion to spiking neuronal network platforms applied to Atari Breakout game
D Patel, H Hazan, DJ Saunders, HT Siegelmann, R Kozma
Neural Networks 120, 108-115, 2019
92019
The Liquid State Machine is not Robust to Problems in Its Components but Topological Constraints Can Restore Robustness.
H Hazan, LM Manevitz
IJCCI (ICFC-ICNC), 258-264, 2010
82010
Two hemispheres—two networks: a computational model explaining hemispheric asymmetries while reading ambiguous words
O Peleg, L Manevitz, H Hazan, Z Eviatar
Annals of Mathematics and Artificial Intelligence 59 (1), 125-147, 2010
82010
Learning bold response in fmri by reservoir computing
P Avesani, H Hazan, E Koilis, L Manevitz, D Sona
2011 International Workshop on Pattern Recognition in NeuroImaging, 57-60, 2011
72011
Temporal pattern recognition via temporal networks of temporal neurons
A Frid, H Hazan, L Manevitz
2012 IEEE 27th Convention of Electrical and Electronics Engineers in Israel, 1-4, 2012
62012
Early Diagnosis of Parkinson’s Disease via Machine Learning on Speech Data, in 2012 IEEE 27th Convention of Electrical Electronics Engineers in Israel (IEEEI), 2012
H Hazan, D Hilu, L Manevitz, S Sapir
proceedings, 2012
52012
Differences and interactions between cerebral hemispheres when processing ambiguous words
O Peleg, Z Eviatar, H Hazan, L Manevitz
International Workshop on Attention in Cognitive Systems, 367-380, 2007
52007
Lattice map spiking neural networks (LM-SNNs) for clustering and classifying image data
H Hazan, DJ Saunders, DT Sanghavi, H Siegelmann, R Kozma
Annals of Mathematics and Artificial Intelligence, 1-24, 2019
42019
Closed Loop Experiment Manager (CLEM)—an open and inexpensive solution for multichannel electrophysiological recordings and closed loop experiments
H Hazan, NE Ziv
Frontiers in Neuroscience 11, 579, 2017
42017
Classification from generation: Recognizing deep grammatical information during reading from rapid event-related fmri
T Bitan, A Frid, H Hazan, LM Manevitz, H Shalelashvili, Y Weiss
2016 International Joint Conference on Neural Networks (IJCNN), 4637-4642, 2016
42016
Non-parametric temporal modeling of the hemodynamic response function via a liquid state machine
P Avesani, H Hazan, E Koilis, LM Manevitz, D Sona
Neural Networks 70, 61-73, 2015
32015
Recognizing deep grammatical information during reading from event related fMRI
H Shalelashvili, T Bitan, A Frid, H Hazan, S Hertz, Y Weiss, LM Manevitz
2014 IEEE 28th Convention of Electrical & Electronics Engineers in Israel …, 2014
32014
The system can't perform the operation now. Try again later.
Articles 1–20