Hava T. Siegelmann
Affiliations: | Computer Science | University of Massachusetts, Amherst, Amherst, MA |
Area:
Computer Science, Technology of EducationGoogle:
"Hava Siegelmann"Children
Sign in to add traineeAmir Tal | grad student | (Neurotree) | |
Megan M. Olsen | grad student | 2011 | U Mass Amherst |
Kyle I. Harrington | grad student | 2010-2012 | U Mass Amherst |
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Publications
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van de Ven GM, Siegelmann HT, Tolias AS. (2020) Brain-inspired replay for continual learning with artificial neural networks. Nature Communications. 11: 4069 |
Patel D, Hazan H, Saunders DJ, et al. (2019) Improved robustness of reinforcement learning policies upon conversion to spiking neuronal network platforms applied to Atari Breakout game. Neural Networks : the Official Journal of the International Neural Network Society |
Saunders DJ, Patel D, Hazan H, et al. (2019) Locally connected spiking neural networks for unsupervised feature learning. Neural Networks : the Official Journal of the International Neural Network Society. 119: 332-340 |
Hazan H, Saunders DJ, Sanghavi DT, et al. (2019) Lattice map spiking neural networks (LM-SNNs) for clustering and classifying image data Annals of Mathematics and Artificial Intelligence. 1-24 |
Hazan H, Saunders DJ, Khan H, et al. (2018) BindsNET: A Machine Learning-Oriented Spiking Neural Networks Library in Python. Frontiers in Neuroinformatics. 12: 89 |
Kozma R, Ilin R, Siegelmann HT. (2018) Evolution of Abstraction Across Layers in Deep Learning Neural Networks Procedia Computer Science. 144: 203-213 |
Burroni J, Taylor P, Corey C, et al. (2017) Energetic Constraints Produce Self-sustained Oscillatory Dynamics in Neuronal Networks. Frontiers in Neuroscience. 11: 80 |
Taylor P, Hobbs JN, Burroni J, et al. (2015) The global landscape of cognition: hierarchical aggregation as an organizational principle of human cortical networks and functions. Scientific Reports. 5: 18112 |
Cabessa J, Siegelmann HT. (2014) The super-Turing computational power of plastic recurrent neural networks. International Journal of Neural Systems. 24: 1450029 |
Tal A, Peled N, Siegelmann HT. (2014) Biologically inspired load balancing mechanism in neocortical competitive learning. Frontiers in Neural Circuits. 8: 18 |