Andrew Saxe

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	Toate	Din 2019
Referințe bibliografice	8617	6839
h-index	28	27
i10-index	43	40

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Surya GanguliAssociate Professor, Stanford UniversityAdresă de e-mail confirmată pe stanford.edu
James L. McClellandStanford UniversityAdresă de e-mail confirmată pe stanford.edu
Madhu AdvaniHarvard UniversityAdresă de e-mail confirmată pe fas.harvard.edu
Andrew NgStanford UniversityAdresă de e-mail confirmată pe cs.stanford.edu
David CoxVP, AI Models; IBM Director, MIT-IBM Watson AI Lab, IBM ResearchAdresă de e-mail confirmată pe ibm.com
Ian GoodfellowDeepMindAdresă de e-mail confirmată pe deepmind.com
Yamini BansalGoogle DeepMindAdresă de e-mail confirmată pe google.com
Benjamin RosmanProfessor at the University of the Witwatersrand, South AfricaAdresă de e-mail confirmată pe wits.ac.za
Jonathan D. CohenProfessor of NeuroscienceAdresă de e-mail confirmată pe princeton.edu
Artemy KolchinskyUniversitat Pompeu FabraAdresă de e-mail confirmată pe upf.edu
Brendan TraceyDeepMindAdresă de e-mail confirmată pe google.com
Joel DapelloSenior Machine Learning EngineerAdresă de e-mail confirmată pe altoslabs.com
Oriol VinyalsResearch Scientist at Google DeepMindAdresă de e-mail confirmată pe google.com
Honglak LeeLG AI Research / U. MichiganAdresă de e-mail confirmată pe umich.edu
Quoc V. LeResearch Scientist, GoogleAdresă de e-mail confirmată pe stanford.edu
Pang Wei KohUniversity of WashingtonAdresă de e-mail confirmată pe cs.washington.edu
Zhenghao ChenCalico Life SciencesAdresă de e-mail confirmată pe cs.stanford.edu
Adam EarleUniversity of the WitwatersrandAdresă de e-mail confirmată pe students.wits.ac.za
Ritvik MudurAdresă de e-mail confirmată pe google.com
Fuat BalcıProfessor of Biological Sciences, University of ManitobaAdresă de e-mail confirmată pe umanitoba.ca

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Andrew Saxe

Professor, Gatsby Unit & Sainsbury Wellcome Centre, UCL

Adresă de e-mail confirmată pe ucl.ac.uk - Pagina de pornire

Theoretical Neuroscience Machine Learning Psychology


Titlu Sortați după descrierea bibliografică Sortați după an Sortați după titlu	Citat de Citat de	Anul
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	2235	2013
A deep learning framework for neuroscience BA Richards, TP Lillicrap, P Beaudoin, Y Bengio, R Bogacz, ... Nature neuroscience 22 (11), 1761-1770, 2019	936	2019
On the information bottleneck theory of deep learning AM Saxe, Y Bansal, J Dapello, M Advani, A Kolchinsky, BD Tracey, ... Journal of Statistical Mechanics: Theory and Experiment 2019 (12), 124020, 2019	656	2019
Qualitatively characterizing neural network optimization problems IJ Goodfellow, O Vinyals, AM Saxe arXiv preprint arXiv:1412.6544, 2014	632	2014
Measuring invariances in deep networks I Goodfellow, H Lee, Q Le, A Saxe, A Ng Advances in neural information processing systems 22, 2009	603	2009
On random weights and unsupervised feature learning. AM Saxe, PW Koh, Z Chen, M Bhand, B Suresh, AY Ng Icml 2 (3), 6, 2011	548	2011
High-dimensional dynamics of generalization error in neural networks MS Advani, AM Saxe, H Sompolinsky Neural Networks 132, 428-446, 2020	524	2020
If deep learning is the answer, what is the question? A Saxe, S Nelli, C Summerfield Nature Reviews Neuroscience 22 (1), 55-67, 2021	343	2021
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
Acquisition of decision making criteria: reward rate ultimately beats accuracy F Balci, P Simen, R Niyogi, A Saxe, JA Hughes, P Holmes, JD Cohen Attention, Perception, & Psychophysics 73, 640-657, 2011	213	2011
Orthogonal representations for robust context-dependent task performance in brains and neural networks T Flesch, K Juechems, T Dumbalska, A Saxe, C Summerfield Neuron 110 (7), 1258-1270. e11, 2022	193*	2022
Dynamics of stochastic gradient descent for two-layer neural networks in the teacher-student setup S Goldt, M Advani, AM Saxe, F Krzakala, L Zdeborová Advances in neural information processing systems 32, 2019	167	2019
Deterministic matrices matching the compressed sensing phase transitions of Gaussian random matrices H Monajemi, S Jafarpour, M Gavish, Stat 330/CME 362 Collaboration, ... Proceedings of the National Academy of Sciences 110 (4), 1181-1186, 2013	126	2013
Multitasking capability versus learning efficiency in neural network architectures S Musslick, A Saxe, K Özcimder, B Dey, G Henselman, JD Cohen Cognitive Science Society, 2017	92	2017
Learning hierarchical category structure in deep neural networks AM Saxe, JL McClelland, S Ganguli Proceedings of the 35th annual meeting of the Cognitive Science Society …, 2013	77*	2013
Energy–entropy competition and the effectiveness of stochastic gradient descent in machine learning Y Zhang, AM Saxe, MS Advani, AA Lee Molecular Physics 116 (21-22), 3214-3223, 2018	76	2018
Continual learning in the teacher-student setup: Impact of task similarity S Lee, S Goldt, A Saxe International Conference on Machine Learning, 6109-6119, 2021	73	2021
Unsupervised learning models of primary cortical receptive fields and receptive field plasticity A Saxe, M Bhand, R Mudur, B Suresh, AY Ng Shawe-Taylor, J.; Zemel, R.; Bartlett, P, 2011	64	2011
Organizing memories for generalization in complementary learning systems W Sun, M Advani, N Spruston, A Saxe, JE Fitzgerald Nature neuroscience 26 (8), 1438-1448, 2023	57	2023
Active long term memory networks T Furlanello, J Zhao, AM Saxe, L Itti, BS Tjan arXiv preprint arXiv:1606.02355, 2016	55	2016

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