Surya Ganguli

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Ben PooleResearch Scientist at Google BrainVerified email at stanford.edu
Jascha Sohl-DicksteinGoogle BrainVerified email at google.com
Niru MaheswaranathanMeta Reality LabsVerified email at fb.com
Aran NayebiICoN Postdoctoral Fellow, MITVerified email at mit.edu
Daniel YaminsAssistant Professor of Computer Science and Psychology, Stanford UniversityVerified email at stanford.edu
Andrew SaxeGatsby Unit & Sainsbury Wellcome Centre, UCLVerified email at ucl.ac.uk
Subhaneil LahiriPostdoctoral Researcher, Department of Applied Physics, Stanford UniversityVerified email at stanford.edu
James L. McClellandStanford UniversityVerified email at stanford.edu
Sam OckoStanfordVerified email at mit.edu
Haim SompolinskyProfessor of Molecular and Cellular Biology and of Physics, Harvard UniversityVerified email at mcb.harvard.edu
Jonathan KadmonThe Hebrew UniversityVerified email at mail.huji.ac.il
Alex H WilliamsNew York University & Flatiron InstituteVerified email at nyu.edu
Yoshua BengioProfessor of computer science, University of Montreal, Mila, IVADO, CIFARVerified email at umontreal.ca
Stephen BaccusProfessor of Neurobiology, Stanford UniversityVerified email at stanford.edu
Mark J. SchnitzerProfessor, HHMI Investigator, Stanford UniversityVerified email at stanford.edu
Daniel KuninStanford UniversityVerified email at stanford.edu
David SussilloMeta Reality Labs and Adjunct Professor @ StanfordVerified email at stanford.edu
Maithra RaghuCornell University and Google BrainVerified email at cornell.edu
Kiah HardcastlePostdoctoral Scientist (Neuroscience), Harvard UniversityVerified email at fas.harvard.edu
Hidenori TanakaHarvard University / NTT Physics & Informatics LabVerified email at fas.harvard.edu

Surya Ganguli

Associate Professor, Stanford University

Verified email at stanford.edu - Homepage

Neuroscience Physics Machine Learning


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Exact solutions to the nonlinear dynamics of learning in deep linear neural networks AM Saxe, JL McClelland, S Ganguli arXiv preprint arXiv:1312.6120, 2013	1630	2013
Continual learning through synaptic intelligence F Zenke, B Poole, S Ganguli International conference on machine learning, 3987-3995, 2017	1554	2017
Identifying and attacking the saddle point problem in high-dimensional non-convex optimization YN Dauphin, R Pascanu, C Gulcehre, K Cho, S Ganguli, Y Bengio Advances in neural information processing systems 27, 2014	1477	2014
Deep knowledge tracing C Piech, J Bassen, J Huang, S Ganguli, M Sahami, LJ Guibas, ... Advances in neural information processing systems 28, 2015	934	2015
Deep unsupervised learning using nonequilibrium thermodynamics J Sohl-Dickstein, E Weiss, N Maheswaranathan, S Ganguli International Conference on Machine Learning, 2256-2265, 2015	711	2015
On the expressive power of deep neural networks M Raghu, B Poole, J Kleinberg, S Ganguli, J Sohl-Dickstein international conference on machine learning, 2847-2854, 2017	682	2017
A deep learning framework for neuroscience BA Richards, TP Lillicrap, P Beaudoin, Y Bengio, R Bogacz, ... Nature neuroscience 22 (11), 1761-1770, 2019	566	2019
Exponential expressivity in deep neural networks through transient chaos B Poole, S Lahiri, M Raghu, J Sohl-Dickstein, S Ganguli Advances in neural information processing systems, 3360-3368, 2016	468	2016
Superspike: Supervised learning in multilayer spiking neural networks F Zenke, S Ganguli Neural computation 30 (6), 1514-1541, 2018	395	2018
Memory traces in dynamical systems S Ganguli, D Huh, H Sompolinsky Proceedings of the national academy of sciences 105 (48), 18970-18975, 2008	337	2008
Cortical layer–specific critical dynamics triggering perception JH Marshel, YS Kim, TA Machado, S Quirin, B Benson, J Kadmon, C Raja, ... Science 365 (6453), eaaw5202, 2019	321	2019
On simplicity and complexity in the brave new world of large-scale neuroscience P Gao, S Ganguli Current opinion in neurobiology 32, 148-155, 2015	297	2015
Deep information propagation SS Schoenholz, J Gilmer, S Ganguli, J Sohl-Dickstein arXiv preprint arXiv:1611.01232, 2016	285	2016
Compressed sensing, sparsity, and dimensionality in neuronal information processing and data analysis S Ganguli, H Sompolinsky Annual review of neuroscience 35, 485-508, 2012	263	2012
Pruning neural networks without any data by iteratively conserving synaptic flow H Tanaka, D Kunin, DL Yamins, S Ganguli Advances in neural information processing systems 33, 6377-6389, 2020	258	2020
Deep learning models of the retinal response to natural scenes L McIntosh, N Maheswaranathan, A Nayebi, S Ganguli, S Baccus Advances in neural information processing systems, 1369-1377, 2016	224	2016
Resurrecting the sigmoid in deep learning through dynamical isometry: theory and practice J Pennington, S Schoenholz, S Ganguli Advances in neural information processing systems 30, 2017	219	2017
Environmental boundaries as an error correction mechanism for grid cells K Hardcastle, S Ganguli, LM Giocomo Neuron 86 (3), 827-839, 2015	211	2015
Unsupervised discovery of demixed, low-dimensional neural dynamics across multiple timescales through tensor component analysis AH Williams, TH Kim, F Wang, S Vyas, SI Ryu, KV Shenoy, M Schnitzer, ... Neuron 98 (6), 1099-1115. e8, 2018	200	2018
A multiplexed, heterogeneous, and adaptive code for navigation in medial entorhinal cortex K Hardcastle, N Maheswaranathan, S Ganguli, LM Giocomo Neuron 94 (2), 375-387. e7, 2017	193	2017

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