David Sussillo

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Krishna V ShenoyStanford and Howard Hughes Medical InstituteEmail yang diverifikasi di stanford.edu
L F AbbottBrandeis University, CERN, Boston University, Columbia University, Stanford Linear AcceleratorEmail yang diverifikasi di columbia.edu
Sergey D. StaviskyAssistant Professor, University of California, DavisEmail yang diverifikasi di ucdavis.edu
Jonathan KaoUniversity of California, Los AngelesEmail yang diverifikasi di seas.ucla.edu
Matthew GolubAssistant ProfessorEmail yang diverifikasi di cs.washington.edu
Valerio ManteUniversity of ZurichEmail yang diverifikasi di ini.uzh.ch
Matthew T KaufmanAssistant Professor at University of ChicagoEmail yang diverifikasi di uchicago.edu
Surya GanguliAssociate Professor, Stanford UniversityEmail yang diverifikasi di stanford.edu
Niru MaheswaranathanMeta Reality LabsEmail yang diverifikasi di fb.com
Mark ChurchlandProfessor of Neuroscience, Columbia UniversityEmail yang diverifikasi di columbia.edu
William T NewsomeStanford UniversityEmail yang diverifikasi di stanford.edu
Chethan PandarinathEmory University and Georgia Tech, Meta Reality LabsEmail yang diverifikasi di emory.edu
Jasmine CollinsResearch Scientist at Databricks/MosaicMLEmail yang diverifikasi di databricks.com
Jascha Sohl-DicksteinAnthropicEmail yang diverifikasi di anthropic.com
Omri BarakTechnion - Israel Institute of TechnologyEmail yang diverifikasi di tx.technion.ac.il
Laura DriscollStanford UniversityEmail yang diverifikasi di stanford.edu
Daniel YaminsAssociate Professor of Computer Science and of Psychology, Stanford UniversityEmail yang diverifikasi di stanford.edu
Aran NayebiAssistant Professor of Machine Learning, Carnegie Mellon University (CMU)Email yang diverifikasi di cs.cmu.edu
Paul NuyujukianStanford UniversityEmail yang diverifikasi di stanford.edu
Jaimie M. HendersonProfessor of Neurosurgery, Stanford UniversityEmail yang diverifikasi di stanford.edu

Ikuti

David Sussillo

Meta Reality Labs and Adjunct Professor @ Stanford

Email yang diverifikasi di stanford.edu

Computational Neuroscience NeuroAI Dynamical Systems


Judul Urutkan menurut kutipan Urutkan menurut tahun Urutkan menurut judul	Dikutip oleh Dikutip oleh	Tahun
Context-dependent computation by recurrent dynamics in prefrontal cortex V Mante, D Sussillo, KV Shenoy, WT Newsome nature 503 (7474), 78, 2013	1824	2013
Generating coherent patterns of activity from chaotic neural networks D Sussillo, LF Abbott Neuron 63 (4), 544-557, 2009	1267	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	709	2018
Computation through neural population dynamics S Vyas, MD Golub, D Sussillo, KV Shenoy Annual review of neuroscience 43 (1), 249-275, 2020	619	2020
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	605	2015
Opening the black box: low-dimensional dynamics in high-dimensional recurrent neural networks D Sussillo, O Barak Neural computation 25 (3), 626-649, 2013	571	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	403	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	308	2007
Neural circuits as computational dynamical systems D Sussillo Current opinion in neurobiology 25, 156-163, 2014	291	2014
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	254*	2023
Capacity and trainability in recurrent neural networks J Collins, J Sohl-Dickstein, D Sussillo arXiv preprint arXiv:1611.09913, 2016	241	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	226	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	220	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	208	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	205	2016
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	186	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	178*	2016
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	160	2019
Random walks: Training very deep nonlin-ear feed-forward networks with smart ini D Sussillo arXiv preprint arXiv 1412, 2014	153*	2014
Hallucinations in neural machine translation K Lee, O Firat, A Agarwal, C Fannjiang, D Sussillo	148	2018

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