Spikes, synchrony, and attentive learning by laminar thalamocortical circuits S Grossberg, M Versace Brain research 1218, 278-312, 2008 | 187 | 2008 |
Predicting the exchange traded fund DIA with a combination of genetic algorithms and neural networks M Versace, R Bhatt, O Hinds, M Shiffer Expert systems with applications 27 (3), 417-425, 2004 | 184 | 2004 |
Methods and apparatus for autonomous robotic control M Versace, A Gorshechnikov, G Livitz, J Palma US Patent 9,626,566, 2017 | 181 | 2017 |
From synapses to circuitry: Using memristive memory to explore the electronic brain G Snider, R Amerson, D Carter, H Abdalla, MS Qureshi, J Léveillé, ... Computer 44 (2), 21-28, 2011 | 132 | 2011 |
The brain of a new machine M Versace, B Chandler IEEE spectrum 47 (12), 30-37, 2010 | 106 | 2010 |
MoNETA: A mind made from memristors M Versace, B Chandler IEEE Spectrum 47 (12), 30-37, 2010 | 63 | 2010 |
Systems and methods to enable continual, memory-bounded learning in artificial intelligence and deep learning continuously operating applications across networked compute edges M Luciw, S Olivera, A Gorshechnikov, J Wurbs, HM Ames, M Versace US Patent 11,928,602, 2024 | 61 | 2024 |
Methods and apparatus for early sensory integration and robust acquisition of real world knowledge A Gorshechnikov, M Versace, T Barnes US Patent 10,300,603, 2019 | 55 | 2019 |
Graphic processor based accelerator system and method A Gorchetchnikov, HM Ames, M Versace, F Santini US Patent 8,648,867, 2014 | 47 | 2014 |
Apparatuses, methods and systems for defining hardware-agnostic brains for autonomous robots M Versace, R Matus, A Defreitas, JM Amadeo, T Seemann, E Marsh, ... US Patent App. 15/343,673, 2017 | 45 | 2017 |
CARTMAP: a neural network method for automated feature selection in financial time series forecasting C Wong, M Versace Neural Computing and Applications 21, 969-977, 2012 | 40 | 2012 |
How do object reference frames and motion vector decomposition emerge in laminar cortical circuits? S Grossberg, J Léveillé, M Versace Attention, Perception, & Psychophysics 73, 1147-1170, 2011 | 31 | 2011 |
A model of STDP based on spatially and temporally local information: Derivation and combination with gated decay A Gorchetchnikov, M Versace, ME Hasselmo Neural Networks 18 (5-6), 458-466, 2005 | 31 | 2005 |
Running as fast as it can: How spiking dynamics form object groupings in the laminar circuits of visual cortex J Léveillé, M Versace, S Grossberg Journal of Computational Neuroscience 28 (2), 323-346, 2010 | 27 | 2010 |
KInNeSS: A modular framework for computational neuroscience M Versace, H Ames, J Léveillé, B Fortenberry, A Gorchetchnikov Neuroinformatics 6, 291-309, 2008 | 26 | 2008 |
Persistence and storage of activity patterns in spiking recurrent cortical networks: modulation of sigmoid signals by after-hyperpolarization currents and acetylcholine J Palma, S Grossberg, M Versace Frontiers in Computational Neuroscience 6, 42, 2012 | 21 | 2012 |
Persuading computers to act more like brains H Ames, M Versace, A Gorchetchnikov, B Chandler, G Livitz, J Léveillé, ... Advances in neuromorphic memristor science and applications, 37-61, 2012 | 18 | 2012 |
A neural network-based exploratory learning and motor planning system for co-robots BV Galbraith, FH Guenther, M Versace Frontiers in Neurorobotics 9, 7, 2015 | 17 | 2015 |
The animat: New frontiers in whole brain modeling H Ames, E Mingolla, A Sohail, B Chandler, A Gorchetchnikov, J Léveillé, ... IEEE pulse 3 (1), 47-50, 2012 | 17 | 2012 |
From spikes to interareal synchrony: how attentive matching and resonance control learning and information processing by laminar thalamocortical circuits M Versace Atlanta, GA: Society for Neuroscience Abstract, 2006, 2006 | 17 | 2006 |