| 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 | 627 | 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 | 560 | 2018 |
| Fast online deconvolution of calcium imaging data J Friedrich, P Zhou, L Paninski PLOS Computational Biology 13 (3), e1005423, 2017 | 463 | 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 | 406 | 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 | 128 | 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 | 72 | 2017 |
| Spatio-temporal credit assignment in neuronal population learning J Friedrich, R Urbanczik, W Senn PLoS computational biology 7 (6), e1002092, 2011 | 66 | 2011 |
| Goal-directed decision making with spiking neurons J Friedrich, M Lengyel Journal of Neuroscience 36 (5), 1529-1546, 2016 | 64 | 2016 |
| Fast active set methods for online spike inference from calcium imaging J Friedrich, L Paninski Advances In Neural Information Processing Systems 29, 2016 | 59 | 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 | 51 | 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 | 47 | 2014 |
| Online analysis of microendoscopic 1-photon calcium imaging data streams J Friedrich, A Giovannucci, EA Pnevmatikakis PLoS computational biology 17 (1), e1008565, 2021 | 32 | 2021 |
| Dynamics of recurrent neural networks with delayed unreliable synapses: metastable clustering J Friedrich, W Kinzel Journal of computational neuroscience 27, 65-80, 2009 | 32 | 2009 |
| 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 | 28 | 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 | 25 | 2020 |
| 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 | 17 | 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 |
| Caiman: An open source toolbox for large scale calcium imaging data analysis on standalone machines A Giovannucci, J Friedrich, B Deverett, V Staneva, D Chklovskii, ... Cosyne Abstracts, 2017 | 11 | 2017 |
| 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 | 11 | 2015 |
| 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 | 9 | 2021 |
Liam PaninskiColumbia UniversityVerified email at stat.columbia.edu
