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Investigating the role of firing-rate normalization and dimensionality reduction in brain-machine interface robustness.

J. Kao, P. Nuyujukian, S. Stavisky, S. Ryu, S. Ganguli, and K. Shenoy. EMBC, page 293-298. IEEE, (2013)

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Short-term memory in neuronal networks through dynamical compressed sensing.S. Ganguli, and H. Sompolinsky. NIPS, page 667-675. Curran Associates, Inc., (2010)On the Expressive Power of Deep Neural Networks.M. Raghu, B. Poole, J. Kleinberg, S. Ganguli, and J. Sohl-Dickstein. ICML, volume 70 of Proceedings of Machine Learning Research, page 2847-2854. PMLR, (2017)SuperSpike: Supervised Learning in Multilayer Spiking Neural Networks.F. Zenke, and S. Ganguli. Neural Computation, (2018)Deep Knowledge Tracing.C. Piech, J. Bassen, J. Huang, S. Ganguli, M. Sahami, L. Guibas, and J. Sohl-Dickstein. NIPS, page 505-513. (2015)Reverse engineering recurrent networks for sentiment classification reveals line attractor dynamics.N. Maheswaranathan, A. Williams, M. Golub, S. Ganguli, and D. Sussillo. NeurIPS, page 15670-15679. (2019)Random projections of random manifolds.S. Lahiri, P. Gao, and S. Ganguli. CoRR, (2016)Identifying and attacking the saddle point problem in high-dimensional non-convex optimization.Y. Dauphin, R. Pascanu, Ç. Gülçehre, K. Cho, S. Ganguli, and Y. Bengio. CoRR, (2014)On the saddle point problem for non-convex optimization.R. Pascanu, Y. Dauphin, S. Ganguli, and Y. Bengio. CoRR, (2014)Role of the site of synaptic competition and the balance of learning forces for Hebbian encoding of probabilistic Markov sequences.K. Bouchard, S. Ganguli, and M. Brainard. Front. Comput. Neurosci., (2015)Exact solutions to the nonlinear dynamics of learning in deep linear neural networks.A. Saxe, J. McClelland, and S. Ganguli. ICLR, (2014)

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Investigating the role of firing-rate normalization and dimensionality reduction in brain-machine interface robustness.

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copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML Investigating the role of firing-rate normalization and dimensionality reduction in brain-machine interface robustness.

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Investigating the role of firing-rate normalization and dimensionality reduction in brain-machine interface robustness.