Encoding and decoding in parietal cortex during sensorimotor decision-making IM Park, MLR Meister, AC Huk, JW Pillow Nature neuroscience 17 (10), 1395-1403, 2014 | 297 | 2014 |
An information theoretic approach of designing sparse kernel adaptive filters W Liu, I Park, JC Príncipe Neural Networks, IEEE Transactions on 20 (12), 1950-1961, 2009 | 264 | 2009 |
Extended kernel recursive least squares algorithm W Liu, I Park, Y Wang, JC Príncipe Signal Processing, IEEE Transactions on 57 (10), 3801-3814, 2009 | 236 | 2009 |
Black box variational inference for state space models E Archer, IM Park, L Buesing, J Cunningham, L Paninski arXiv preprint arXiv:1511.07367, 2015 | 172 | 2015 |
Variational latent gaussian process for recovering single-trial dynamics from population spike trains Y Zhao, IM Park Neural computation 29 (5), 1293-1316, 2017 | 135 | 2017 |
A reproducing kernel hilbert space framework for spike train signal processing ARC Paiva, I Park, JC Príncipe Neural computation 21 (2), 424-449, 2009 | 113 | 2009 |
Functional dissection of signal and noise in MT and LIP during decision-making JL Yates, IM Park, LN Katz, JW Pillow, AC Huk Nature neuroscience 20 (9), 1285-1292, 2017 | 111 | 2017 |
Bayesian entropy estimation for countable discrete distributions E Archer, IM Park, JW Pillow The Journal of Machine Learning Research 15 (1), 2833-2868, 2014 | 107 | 2014 |
A comparison of binless spike train measures ARC Paiva, I Park, JC Príncipe Neural computing & applications 19 (3), 405-419, 2010 | 87 | 2010 |
A reproducing kernel Hilbert space framework for information-theoretic learning JW Xu, ARC Paiva, I Park, JC Principe Signal Processing, IEEE Transactions on 56 (12), 5891-5902, 2008 | 86 | 2008 |
Bayesian Spike-Triggered Covariance Analysis IM Park, JW Pillow Advances in neural information processing systems (NIPS), 2011 | 84 | 2011 |
Tree-structured recurrent switching linear dynamical systems for multi-scale modeling J Nassar, S Linderman, M Bugallo, IM Park International Conference on Learning Representation (ICLR) 2019, 2018 | 75 | 2018 |
Kernel methods on spike train space for neuroscience: a tutorial IM Park, S Seth, ARC Paiva, L Li, JC Principe IEEE Signal Processing Magazine 30 (4), 149-160, 2013 | 74 | 2013 |
Liquid state machines and cultured cortical networks: The separation property KP Dockendorf, I Park, P He, JC Príncipe, TB DeMarse Biosystems 95 (2), 90-97, 2009 | 74 | 2009 |
Spectral methods for neural characterization using generalized quadratic models IM Park, EW Archer, N Priebe, JW Pillow Advances in neural information processing systems 26, 2013 | 72 | 2013 |
Neural latents benchmark'21: evaluating latent variable models of neural population activity F Pei, J Ye, D Zoltowski, A Wu, RH Chowdhury, H Sohn, JE O'Doherty, ... arXiv preprint arXiv:2109.04463, 2021 | 64 | 2021 |
Gated recurrent units viewed through the lens of continuous time dynamical systems ID Jordan, PA Sokol, IM Park arXiv preprint arXiv:1906.01005, 2019 | 56 | 2019 |
Bayesian efficient coding IM Park, JW Pillow BioRxiv, 178418, 2017 | 56 | 2017 |
Bayesian and quasi-Bayesian estimators for mutual information from discrete data E Archer, IM Park, JW Pillow Entropy 15 (5), 1738-1755, 2013 | 52 | 2013 |
Bayesian entropy estimation for binary spike train data using parametric prior knowledge EW Archer, IM Park, JW Pillow Advances in neural information processing systems 26, 2013 | 42 | 2013 |