Zobrazeno 1 - 9 of 9 pro vyhledávání: '"David D'Onofrio"'
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Akademický článek
Training spiking neuronal networks to perform motor control using reinforcement and evolutionary learning
Autor: Daniel Haşegan, Matt Deible, Christopher Earl, David D’Onofrio, Hananel Hazan, Haroon Anwar, Samuel A. Neymotin
Publikováno v: Frontiers in Computational Neuroscience, Vol 16 (2022)
Artificial neural networks (ANNs) have been successfully trained to perform a wide range of sensory-motor behaviors. In contrast, the performance of spiking neuronal network (SNN) models trained to perform similar behaviors remains relatively subopti
Externí odkaz: https://doaj.org/article/e48300e666124b53b4fabec9e6c8dc41
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3
Akademický článek
Training a spiking neuronal network model of visual-motor cortex to play a virtual racket-ball game using reinforcement learning
Autor: Haroon Anwar, Simon Caby, Salvador Dura-Bernal, David D’Onofrio, Daniel Hasegan, Matt Deible, Sara Grunblatt, George L. Chadderdon, Cliff C. Kerr, Peter Lakatos, William W. Lytton, Hananel Hazan, Samuel A. Neymotin
Publikováno v: PLoS ONE, Vol 17, Iss 5 (2022)
Recent models of spiking neuronal networks have been trained to perform behaviors in static environments using a variety of learning rules, with varying degrees of biological realism. Most of these models have not been tested in dynamic visual enviro
Externí odkaz: https://doaj.org/article/1b4f56c6ca6644df967cc5c65d03cb5f
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4
Evolutionary and spike-timing-dependent reinforcement learning train spiking neuronal network motor control
Autor: Christopher Earl, Matt Deible, Samuel A. Neymotin, Haroon Anwar, Daniel Hasegan, David D’Onofrio, Hananel Hazan
Biological learning operates at multiple interlocking timescales, from long evolutionary stretches down to the relatively short time span of an individual9s life. While each process has been simulated individually as a basic learning algorithm in the
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::ad21e007ccf6fa411bf1054a67d3230f
https://doi.org/10.1101/2021.11.20.469405
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5
Training a spiking neuronal network model of visual-motor cortex to play a virtual racket-ball game using reinforcement learning
Autor: Haroon Anwar, Simon Caby, Salvador Dura-Bernal, David D’Onofrio, Daniel Hasegan, Matt Deible, Sara Grunblatt, George L. Chadderdon, Cliff C. Kerr, Peter Lakatos, William W. Lytton, Hananel Hazan, Samuel A. Neymotin
Publikováno v: PloS one. 17(5)
Recent models of spiking neuronal networks have been trained to perform behaviors in static environments using a variety of learning rules, with varying degrees of biological realism. Most of these models have not been tested in dynamic visual enviro
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5e2a72ea4d21ff4cd12c27d160ce0c38
https://pubmed.ncbi.nlm.nih.gov/35544518
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8
Calibrating R-LINE model results with observational data to develop annual mobile source air pollutant fields at fine spatial resolution: Application in Atlanta
Autor: Armistead G. Russell, James A. Mulholland, Poornima Sampath, David D'Onofrio, Xinxin Zhai, Yunhee Kim, Byeong-Uk Kim
Publikováno v: Atmospheric Environment. 147:446-457
The Research LINE-source (R-LINE) dispersion model for near-surface releases is a dispersion model developed to estimate the impacts of line sources, such as automobiles, on primary air pollutant levels. In a multiyear application in Atlanta, R-LINE
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b9c8a51e362c169fcc3fb2f0e42c631e
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