Johannes Friedrich

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Liam PaninskiColumbia UniversityEmail yang diverifikasi di stat.columbia.edu
Eftychios A. PnevmatikakisMeta Reality LabsEmail yang diverifikasi di flatironinstitute.org
Andrea GiovannucciSenior Principal Scientist. Bristol Myers Squibb.Email yang diverifikasi di bms.com
Pengcheng ZhouShenzhen Institute of Advanced Technology, Chinese Academy of SciencesEmail yang diverifikasi di siat.ac.cn
Dmitri "Mitya" B. ChklovskiiFlatiron Institute, Simons Foundation and NYUEmail yang diverifikasi di flatironinstitute.org
David W. TankPrinceton UniversityEmail yang diverifikasi di princeton.edu
Sue Ann KoayJaneliaEmail yang diverifikasi di janelia.hhmi.org
Farzaneh NajafiAssistant Professor at Georgia TechEmail yang diverifikasi di gatech.edu
BERNARDO SABATINIPROFESSOR OF NEUROBIOLOGY, HHMI, HARVARD MEDICAL SCHOOLEmail yang diverifikasi di HMS.HARVARD.EDU
Yu MuInstitute of Neuroscience, Chinese Academy of SciencesEmail yang diverifikasi di ion.ac.cn
Daniel SoudryAssociate ProfessorEmail yang diverifikasi di technion.ac.il
Máté LengyelProfessor of Computational Neuroscience, University of Cambridge; Senior Research Fellow, CEUEmail yang diverifikasi di eng.cam.ac.uk
Darcy S. PeterkaColumbia UniversityEmail yang diverifikasi di columbia.edu
Weijian YangUniversity of California, Davis; University of California, Berkeley; Columbia UniversityEmail yang diverifikasi di ucdavis.edu
Rafael YusteDirector, Neurotechnology Center, Columbia UniversityEmail yang diverifikasi di columbia.edu
Elisa M TartagliaInstitut de la Vision/ UPMCEmail yang diverifikasi di inserm.fr
Aaron ClarkeBilkent UniversityEmail yang diverifikasi di bilkent.edu.tr
Wolfgang KinzelProfessor für Theoretische PhysikEmail yang diverifikasi di physik.uni-wuerzburg.de

Ikuti

Johannes Friedrich

Allen Institute for Neural Dynamics

Email yang diverifikasi di columbia.edu - Beranda

Neural Data Science Calcium Imaging Computational Neuroscience Machine Learning Reinforcement Learning


Judul Urutkan menurut kutipan Urutkan menurut tahun Urutkan menurut judul	Dikutip oleh Dikutip oleh	Tahun
CaImAn an open source tool for scalable calcium imaging data analysis A Giovannucci, J Friedrich, P Gunn, J Kalfon, BL Brown, SA Koay, ... elife 8, e38173, 2019	807	2019
Efficient and accurate extraction of in vivo calcium signals from microendoscopic video data P Zhou, SL Resendez, J Rodriguez-Romaguera, JC Jimenez, SQ Neufeld, ... elife 7, e28728, 2018	669	2018
Fast online deconvolution of calcium imaging data J Friedrich, P Zhou, L Paninski PLOS Computational Biology 13 (3), e1005423, 2017	553	2017
Bright and photostable chemigenetic indicators for extended in vivo voltage imaging AS Abdelfattah, T Kawashima, A Singh, O Novak, H Liu, Y Shuai, ... Science 365 (6454), 699-704, 2019	486	2019
Community-based benchmarking improves spike rate inference from two-photon calcium imaging data P Berens, J Freeman, T Deneux, N Chenkov, T McColgan, A Speiser, ... PLoS computational biology 14 (5), e1006157, 2018	150	2018
OnACID: Online Analysis of Calcium Imaging Data in Real Time EAP Andrea Giovannucci, Johannes Friedrich, Matt Kaufman, Anne Churchland ... Advances in Neural Information Processing Systems 30, 2017	84	2017
Goal-directed decision making with spiking neurons J Friedrich, M Lengyel Journal of Neuroscience 36 (5), 1529-1546, 2016	74	2016
Spatio-temporal credit assignment in neuronal population learning J Friedrich, R Urbanczik, W Senn PLoS computational biology 7 (6), e1002092, 2011	69	2011
Fast active set methods for online spike inference from calcium imaging J Friedrich, L Paninski Advances in neural information processing systems 29, 2016	64	2016
Multi-scale approaches for high-speed imaging and analysis of large neural populations J Friedrich, W Yang, D Soudry, Y Mu, MB Ahrens, R Yuste, DS Peterka, ... PLoS computational biology 13 (8), e1005685, 2017	55	2017
Code-specific learning rules improve action selection by populations of spiking neurons J Friedrich, R Urbanczik, W Senn International journal of neural systems 24 (05), 1450002, 2014	48	2014
VolPy: Automated and scalable analysis pipelines for voltage imaging datasets C Cai, J Friedrich, A Singh, MH Eybposh, EA Pnevmatikakis, K Podgorski, ... PLoS computational biology 17 (4), e1008806, 2021	41	2021
Online analysis of microendoscopic 1-photon calcium imaging data streams J Friedrich, A Giovannucci, EA Pnevmatikakis PLoS computational biology 17 (1), e1008565, 2021	41	2021
Blood transfusion and risk of venous thromboembolism: a population-based cohort study SY Lin, YL Chang, HC Yeh, CL Lin, CH Kao Thrombosis and haemostasis 120 (01), 156-167, 2020	35	2020
Dynamics of recurrent neural networks with delayed unreliable synapses: metastable clustering J Friedrich, W Kinzel Journal of computational neuroscience 27, 65-80, 2009	33	2009
Human and machine learning in non-markovian decision making AM Clarke, J Friedrich, EM Tartaglia, S Marchesotti, W Senn, MH Herzog PloS one 10 (4), e0123105, 2015	20	2015
Learning spike-based population codes by reward and population feedback J Friedrich, R Urbanczik, W Senn Neural computation 22 (7), 1698-1717, 2010	17	2010
Neural optimal feedback control with local learning rules J Friedrich, S Golkar, S Farashahi, A Genkin, A Sengupta, D Chklovskii Advances in Neural Information Processing Systems 34, 16358-16370, 2021	15	2021
FIOLA: an accelerated pipeline for fluorescence imaging online analysis C Cai, C Dong, J Friedrich, M Rozsa, EA Pnevmatikakis, A Giovannucci Nature Methods 20 (9), 1417-1425, 2023	13	2023
Fast constrained non-negative matrix factorization for whole-brain calcium imaging data J Friedrich, D Soudry, Y Mu, J Freeman, M Ahrens, L Paninski NIPS workshop on statistical methods for understanding neural systems, 2015	13	2015

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