John Cunningham

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Coauteurs

Krishna V ShenoyStanford & HHMIAdresse e-mail validée de stanford.edu
Stephen RyuPalo Alto Medical Foundation / Stanford UniversityAdresse e-mail validée de stanford.edu
Mark ChurchlandProfessor of Neuroscience, Columbia UniversityAdresse e-mail validée de columbia.edu
Byron YuCarnegie Mellon UniversityAdresse e-mail validée de cmu.edu
Paul NuyujukianStanford UniversityAdresse e-mail validée de stanford.edu
Vikash GiljaAssociate Professor, Electrical & Computer Engineering, University of California, San DiegoAdresse e-mail validée de ucsd.edu
Liam PaninskiColumbia UniversityAdresse e-mail validée de stat.columbia.edu
Maneesh SahaniGatsby Unit, UCLAdresse e-mail validée de gatsby.ucl.ac.uk
Matthew T KaufmanAssistant Professor at University of ChicagoAdresse e-mail validée de uchicago.edu
Cynthia ChestekUniversity of MichiganAdresse e-mail validée de umich.edu
Gamaleldin ElsayedResearch Scientist, Google Research, Brain TeamAdresse e-mail validée de google.com
Lars BuesingGoogle DeepMindAdresse e-mail validée de google.com
Jonathan KaoUniversity of California, Los AngelesAdresse e-mail validée de seas.ucla.edu
Elad GilboaAdresse e-mail validée de ese.wustl.edu
Antonio Homero LaraAdresse e-mail validée de columbia.edu
Arye NehoraiWashington University in St. LouisAdresse e-mail validée de ese.wustl.edu
Shreya SaxenaAssistant Professor, Department of Electrical and Computer Engineering, University of FloridaAdresse e-mail validée de ufl.edu
Christian RobertUniversité Paris Dauphine, PSL & University of WarwickAdresse e-mail validée de ceremade.dauphine.fr
Andrew GelmanProfessor of Statistics and Political Science, Columbia UniversityAdresse e-mail validée de stat.columbia.edu
Aki VehtariAssociate Professor, Aalto UniversityAdresse e-mail validée de aalto.fi

John Cunningham

Associate Professor, Columbia University

Adresse e-mail validée de columbia.edu - Page d'accueil

machine learning neuroscience


Titre Trier par citations Trier par année Trier par titre	Citée par Citée par	Année
Neural population dynamics during reaching MM Churchland, JP Cunningham, MT Kaufman, JD Foster, P Nuyujukian, ... Nature 487 (7405), 51-56, 2012	965	2012
Stimulus onset quenches neural variability: a widespread cortical phenomenon MM Churchland, MY Byron, JP Cunningham, LP Sugrue, MR Cohen, ... Nature neuroscience 13 (3), 369-378, 2010	845	2010
Dimensionality reduction for large-scale neural recordings JP Cunningham, MY Byron Nature neuroscience 17 (11), 1500-1509, 2014	573	2014
Influence of heart rate on the BOLD signal: the cardiac response function C Chang, JP Cunningham, GH Glover Neuroimage 44 (3), 857-869, 2009	506	2009
Gaussian-process factor analysis for low-dimensional single-trial analysis of neural population activity BM Yu, JP Cunningham, G Santhanam, SI Ryu, KV Shenoy, M Sahani Journal of neurophysiology 102 (1), 614-635, 2009	482	2009
A high-performance neural prosthesis enabled by control algorithm design V Gilja, P Nuyujukian, CA Chestek, JP Cunningham, MY Byron, JM Fan, ... Nature neuroscience 15 (12), 1752-1757, 2012	418	2012
Linear dimensionality reduction: Survey, insights, and generalizations JP Cunningham, Z Ghahramani The Journal of Machine Learning Research 16 (1), 2859-2900, 2015	381	2015
Cortical preparatory activity: representation of movement or first cog in a dynamical machine? MM Churchland, JP Cunningham, MT Kaufman, SI Ryu, KV Shenoy Neuron 68 (3), 387-400, 2010	314	2010
Long-term stability of neural prosthetic control signals from silicon cortical arrays in rhesus macaque motor cortex CA Chestek, V Gilja, P Nuyujukian, JD Foster, JM Fan, MT Kaufman, ... Journal of neural engineering 8 (4), 045005, 2011	271	2011
Bayesian Optimization with Inequality Constraints. JR Gardner, MJ Kusner, ZE Xu, KQ Weinberger, JP Cunningham ICML 2014, 937-945, 2014	228	2014
Empirical models of spiking in neural populations JH Macke, L Buesing, JP Cunningham, BM Yu, KV Shenoy, M Sahani Advances in Neural Information Processing Systems 24: 25th conference on …, 2012	186	2012
A closed-loop human simulator for investigating the role of feedback control in brain-machine interfaces JP Cunningham, P Nuyujukian, V Gilja, CA Chestek, SI Ryu, KV Shenoy Journal of neurophysiology 105 (4), 1932-1949, 2011	151	2011
Reorganization between preparatory and movement population responses in motor cortex GF Elsayed, AH Lara, MT Kaufman, MM Churchland, JP Cunningham Nature communications 7 (1), 1-15, 2016	146	2016
Single-neuron stability during repeated reaching in macaque premotor cortex CA Chestek, AP Batista, G Santhanam, MY Byron, A Afshar, ... Journal of Neuroscience 27 (40), 10742-10750, 2007	137	2007
Fast Kernel Learning for Multidimensional Pattern Extrapolation. AG Wilson, E Gilboa, JP Cunningham, A Nehorai NIPS, 3626-3634, 2014	131	2014
Single-trial dynamics of motor cortex and their applications to brain-machine interfaces JC Kao, P Nuyujukian, SI Ryu, MM Churchland, JP Cunningham, ... Nature communications 6 (1), 1-12, 2015	118	2015
Black box variational inference for state space models E Archer, IM Park, L Buesing, J Cunningham, L Paninski arXiv preprint arXiv:1511.07367, 2015	107	2015
Linear dynamical neural population models through nonlinear embeddings Y Gao, E Archer, L Paninski, JP Cunningham arXiv preprint arXiv:1605.08454, 2016	100	2016
Fast Gaussian process methods for point process intensity estimation JP Cunningham, KV Shenoy, M Sahani Proceedings of the 25th international conference on Machine learning, 192-199, 2008	95	2008
Methods for estimating neural firing rates, and their application to brain–machine interfaces JP Cunningham, V Gilja, SI Ryu, KV Shenoy Neural Networks 22 (9), 1235-1246, 2009	94	2009

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