David Sussillo

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	Toate	Din 2019
Referințe bibliografice	9305	6819
h-index	34	32
i10-index	43	42

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Krishna V ShenoyStanford and Howard Hughes Medical InstituteAdresă de e-mail confirmată pe stanford.edu
L F AbbottBrandeis University, CERN, Boston University, Columbia University, Stanford Linear AcceleratorAdresă de e-mail confirmată pe columbia.edu
Sergey D. StaviskyAssistant Professor, University of California, DavisAdresă de e-mail confirmată pe ucdavis.edu
Jonathan KaoUniversity of California, Los AngelesAdresă de e-mail confirmată pe seas.ucla.edu
Matthew GolubAssistant ProfessorAdresă de e-mail confirmată pe cs.washington.edu
Matthew T KaufmanAssistant Professor at University of ChicagoAdresă de e-mail confirmată pe uchicago.edu
Surya GanguliAssociate Professor, Stanford UniversityAdresă de e-mail confirmată pe stanford.edu
Valerio ManteUniversity of ZurichAdresă de e-mail confirmată pe ini.uzh.ch
Niru MaheswaranathanMeta Reality LabsAdresă de e-mail confirmată pe fb.com
Mark ChurchlandProfessor of Neuroscience, Columbia UniversityAdresă de e-mail confirmată pe columbia.edu
William T NewsomeStanford UniversityAdresă de e-mail confirmată pe stanford.edu
Jasmine CollinsResearch Scientist at Databricks/MosaicMLAdresă de e-mail confirmată pe databricks.com
Jascha Sohl-DicksteinAnthropicAdresă de e-mail confirmată pe anthropic.com
Omri BarakTechnion - Israel Institute of TechnologyAdresă de e-mail confirmată pe tx.technion.ac.il
Chethan PandarinathEmory University and Georgia TechAdresă de e-mail confirmată pe emory.edu
Jonas KubiliusScientist in Residence @ Jones Lab / EMBLAdresă de e-mail confirmată pe gmc.vu.lt
James J DiCarloMassachusetts Institute of TechnologyAdresă de e-mail confirmată pe mit.edu
Daniel BearStanford UniversityAdresă de e-mail confirmată pe stanford.edu
Daniel YaminsAssociate Professor of Computer Science and of Psychology, Stanford UniversityAdresă de e-mail confirmată pe stanford.edu
Aran NayebiAssistant Professor of Machine Learning, Carnegie Mellon University (CMU)Adresă de e-mail confirmată pe cs.cmu.edu

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David Sussillo

Meta Reality Labs and Adjunct Professor @ Stanford

Adresă de e-mail confirmată pe stanford.edu

Computational Neuroscience AI Dynamical Systems


Titlu Sortați după descrierea bibliografică Sortați după an Sortați după titlu	Citat de Citat de	Anul
Context-dependent computation by recurrent dynamics in prefrontal cortex V Mante, D Sussillo, KV Shenoy, WT Newsome nature 503 (7474), 78, 2013	1710	2013
Generating coherent patterns of activity from chaotic neural networks D Sussillo, LF Abbott Neuron 63 (4), 544-557, 2009	1200	2009
Inferring single-trial neural population dynamics using sequential auto-encoders C Pandarinath, DJ O’Shea, J Collins, R Jozefowicz, SD Stavisky, JC Kao, ... Nature methods 15 (10), 805-815, 2018	634	2018
A neural network that finds a naturalistic solution for the production of muscle activity D Sussillo, MM Churchland, MT Kaufman, KV Shenoy Nature neuroscience 18 (7), 1025-1033, 2015	569	2015
Computation through neural population dynamics S Vyas, MD Golub, D Sussillo, KV Shenoy Annual review of neuroscience 43 (1), 249-275, 2020	541	2020
Opening the black box: low-dimensional dynamics in high-dimensional recurrent neural networks D Sussillo, O Barak Neural computation 25 (3), 626-649, 2013	538	2013
Modular propagation of epileptiform activity: evidence for an inhibitory veto in neocortex AJ Trevelyan, D Sussillo, BO Watson, R Yuste The Journal of neuroscience 26 (48), 12447-12455, 2006	395	2006
Feedforward inhibition contributes to the control of epileptiform propagation speed AJ Trevelyan, D Sussillo, R Yuste Journal of Neuroscience 27 (13), 3383-3387, 2007	297	2007
Neural circuits as computational dynamical systems D Sussillo Current opinion in neurobiology 25, 156-163, 2014	276	2014
Capacity and trainability in recurrent neural networks J Collins, J Sohl-Dickstein, D Sussillo arXiv preprint arXiv:1611.09913, 2016	236	2016
A recurrent neural network for closed-loop intracortical brain–machine interface decoders D Sussillo, P Nuyujukian, JM Fan, JC Kao, SD Stavisky, S Ryu, K Shenoy Journal of neural engineering 9 (2), 026027, 2012	211	2012
Making brain–machine interfaces robust to future neural variability D Sussillo, SD Stavisky, JC Kao, SI Ryu, KV Shenoy Nature communications 7 (1), 13749, 2016	198	2016
From fixed points to chaos: three models of delayed discrimination O Barak, D Sussillo, R Romo, M Tsodyks, LF Abbott Progress in neurobiology 103, 214-222, 2013	198	2013
The largest response component in the motor cortex reflects movement timing but not movement type MT Kaufman, JS Seely, D Sussillo, SI Ryu, KV Shenoy, MM Churchland eneuro 3 (4), 2016	197	2016
Catalyzing next-generation artificial intelligence through neuroai A Zador, S Escola, B Richards, B Ölveczky, Y Bengio, K Boahen, ... Nature communications 14 (1), 1597, 2023	194*	2023
Task-driven convolutional recurrent models of the visual system A Nayebi, D Bear, J Kubilius, K Kar, S Ganguli, D Sussillo, JJ DiCarlo, ... Advances in neural information processing systems 31, 2018	176	2018
An online sequence-to-sequence model using partial conditioning N Jaitly, QV Le, O Vinyals, I Sutskever, D Sussillo, S Bengio Advances in neural information processing systems 29, 2016	170*	2016
Random walks: Training very deep nonlin-ear feedforward networks with smart ini D Sussillo arXiv preprint arXiv 1412, 2014	150*	2014
Universality and individuality in neural dynamics across large populations of recurrent networks N Maheswaranathan, A Williams, M Golub, S Ganguli, D Sussillo Advances in neural information processing systems 32, 2019	142	2019
Hallucinations in neural machine translation K Lee, O Firat, A Agarwal, C Fannjiang, D Sussillo	133	2018

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