Paul A. Merolla, Ph.D.

Institution:
University of Pennsylvania, Philadelphia, PA, United States
Area:
Silicon Retinas, Neuromorphic Systems
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"Paul Merolla"
Mean distance: 16.57 (cluster 17)
 

Parents

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Kwabena Boahen grad student 2006 Penn
 (A silicon model of the primary visual cortex: Representing features through stochastic variations.)
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Publications

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Pedroni BU, Das S, Arthur JV, et al. (2016) Mapping Generative Models onto a Network of Digital Spiking Neurons. Ieee Transactions On Biomedical Circuits and Systems
Esser SK, Merolla PA, Arthur JV, et al. (2016) Convolutional networks for fast, energy-efficient neuromorphic computing. Proceedings of the National Academy of Sciences of the United States of America
Pedroni BU, Das S, Arthur JV, et al. (2016) Mapping Generative Models onto a Network of Digital Spiking Neurons. Ieee Transactions On Biomedical Circuits and Systems
Andreopoulos A, Taba B, Cassidy AS, et al. (2015) Visual saliency on networks of neurosynaptic cores Ibm Journal of Research and Development. 59
Akopyan F, Sawada J, Cassidy A, et al. (2015) TrueNorth: Design and Tool Flow of a 65 mW 1 Million Neuron Programmable Neurosynaptic Chip Ieee Transactions On Computer-Aided Design of Integrated Circuits and Systems. 34: 1537-1557
Das S, Pedroni BU, Merolla P, et al. (2015) Gibbs sampling with low-power spiking digital neurons Proceedings - Ieee International Symposium On Circuits and Systems. 2015: 2704-2707
Merolla PA, Arthur JV, Alvarez-Icaza R, et al. (2014) Artificial brains. A million spiking-neuron integrated circuit with a scalable communication network and interface. Science (New York, N.Y.). 345: 668-73
Merolla P, Arthur J, Alvarez R, et al. (2014) A multicast tree router for multichip neuromorphic systems Ieee Transactions On Circuits and Systems I: Regular Papers. 61: 820-833
Cassidy AS, Alvarez-Icaza R, Akopyan F, et al. (2014) Real-Time Scalable Cortical Computing at 46 Giga-Synaptic OPS/Watt with ∼100× Speedup in Time-to-Solution and ∼100,000× Reduction in Energy-to-Solution International Conference For High Performance Computing, Networking, Storage and Analysis, Sc. 2015: 27-38
Benjamin BV, Gao P, McQuinn E, et al. (2014) Neurogrid: A mixed-analog-digital multichip system for large-scale neural simulations Proceedings of the Ieee. 102: 699-716
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