Surya Ganguli

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Niru MaheswaranathanMeta Reality LabsPatvirtintas el. paštas fb.com
Jascha Sohl-DicksteinAnthropicPatvirtintas el. paštas anthropic.com
Ben PooleResearch Scientist at Google DeepMindPatvirtintas el. paštas stanford.edu
Aran NayebiAssistant Professor of Machine Learning, Carnegie Mellon University (CMU)Patvirtintas el. paštas cs.cmu.edu
Daniel YaminsAssociate Professor of Computer Science and of Psychology, Stanford UniversityPatvirtintas el. paštas stanford.edu
Andrew SaxeProfessor, Gatsby Unit & Sainsbury Wellcome Centre, UCLPatvirtintas el. paštas ucl.ac.uk
Subhaneil LahiriResearch Scientist, Department of Applied Physics, Stanford UniversityPatvirtintas el. paštas stanford.edu
Daniel KuninStanford UniversityPatvirtintas el. paštas stanford.edu
Jonathan KadmonThe Hebrew UniversityPatvirtintas el. paštas mail.huji.ac.il
Stephen BaccusProfessor of Neurobiology, Stanford UniversityPatvirtintas el. paštas stanford.edu
Yoshua BengioProfessor of computer science, University of Montreal, Mila, IVADO, CIFARPatvirtintas el. paštas umontreal.ca
Hidenori TanakaGroup Leader, CBS-NTT Physics of Intelligence Program, Harvard UniversityPatvirtintas el. paštas fas.harvard.edu
James L. McClellandStanford UniversityPatvirtintas el. paštas stanford.edu
Sam OckoStanfordPatvirtintas el. paštas mit.edu
Mansheej PaulResearch Scientist, DatabricksPatvirtintas el. paštas databricks.com
Mark J. SchnitzerProfessor, HHMI Investigator, Stanford UniversityPatvirtintas el. paštas stanford.edu
Alex H WilliamsNew York University & Flatiron InstitutePatvirtintas el. paštas nyu.edu
Ben SorscherStanford UniversityPatvirtintas el. paštas stanford.edu
Haim SompolinskyProfessor of Molecular and Cellular Biology and of Physics, Harvard UniversityPatvirtintas el. paštas mcb.harvard.edu
Yann N. DauphinGoogle AIPatvirtintas el. paštas dauphin.io

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Surya Ganguli

Associate Professor, Stanford University

Patvirtintas el. paštas stanford.edu - Pagrindinis puslapis

Neuroscience Physics Machine Learning


Pavadinimas Rūšiuoti pagal šaltinius Rūšiuoti pagal metus Rūšiuoti pagal pavadinimą	Cituota Cituota	Metai
Deep unsupervised learning using nonequilibrium thermodynamics J Sohl-Dickstein, E Weiss, N Maheswaranathan, S Ganguli International conference on machine learning, 2256-2265, 2015	6329	2015
Continual learning through synaptic intelligence F Zenke, B Poole, S Ganguli International conference on machine learning, 3987-3995, 2017	2956	2017
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	2234	2013
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	1869	2014
Deep knowledge tracing C Piech, J Bassen, J Huang, S Ganguli, M Sahami, LJ Guibas, ... Advances in neural information processing systems 28, 2015	1627	2015
Holistic evaluation of language models P Liang, R Bommasani, T Lee, D Tsipras, D Soylu, M Yasunaga, Y Zhang, ... arXiv preprint arXiv:2211.09110, 2022	1103	2022
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	992	2017
A deep learning framework for neuroscience BA Richards, TP Lillicrap, P Beaudoin, Y Bengio, R Bogacz, ... Nature neuroscience 22 (11), 1761-1770, 2019	935	2019
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	708	2020
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	680	2016
Superspike: Supervised learning in multilayer spiking neural networks F Zenke, S Ganguli Neural computation 30 (6), 1514-1541, 2018	670	2018
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	578	2019
Deep information propagation SS Schoenholz, J Gilmer, S Ganguli, J Sohl-Dickstein arXiv preprint arXiv:1611.01232, 2016	431	2016
Deep learning on a data diet: Finding important examples early in training M Paul, S Ganguli, GK Dziugaite Advances in neural information processing systems 34, 20596-20607, 2021	395	2021
Memory traces in dynamical systems S Ganguli, D Huh, H Sompolinsky Proceedings of the national academy of sciences 105 (48), 18970-18975, 2008	391	2008
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	389	2015
Beyond neural scaling laws: beating power law scaling via data pruning B Sorscher, R Geirhos, S Shekhar, S Ganguli, A Morcos Advances in Neural Information Processing Systems 35, 19523-19536, 2022	370	2022
Understanding self-supervised learning dynamics without contrastive pairs Y Tian, X Chen, S Ganguli International Conference on Machine Learning, 10268-10278, 2021	327	2021
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	315	2017
A mathematical theory of semantic development in deep neural networks AM Saxe, JL McClelland, S Ganguli Proceedings of the National Academy of Sciences 116 (23), 11537-11546, 2019	314	2019

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