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Il Memming Park
Il Memming Park
Other names박 일, Il Park
Group Leader, Champalimaud Research; Visiting Associate Professor, Stony Brook University
Verified email at research.fchampalimaud.org - Homepage
Title
Cited by
Cited by
Year
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
3102014
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
2682009
Extended kernel recursive least squares algorithm
W Liu, I Park, Y Wang, JC Príncipe
Signal Processing, IEEE Transactions on 57 (10), 3801-3814, 2009
2382009
Black box variational inference for state space models
E Archer, IM Park, L Buesing, J Cunningham, L Paninski
arXiv preprint arXiv:1511.07367, 2015
1812015
Variational latent gaussian process for recovering single-trial dynamics from population spike trains
Y Zhao, IM Park
Neural computation 29 (5), 1293-1316, 2017
1452017
A reproducing kernel hilbert space framework for spike train signal processing
ARC Paiva, I Park, JC Príncipe
Neural computation 21 (2), 424-449, 2009
1162009
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
1152017
Bayesian entropy estimation for countable discrete distributions
E Archer, IM Park, JW Pillow
The Journal of Machine Learning Research 15 (1), 2833-2868, 2014
1112014
A comparison of binless spike train measures
ARC Paiva, I Park, JC Príncipe
Neural computing & applications 19 (3), 405-419, 2010
882010
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
882008
Bayesian Spike-Triggered Covariance Analysis
IM Park, JW Pillow
Advances in neural information processing systems (NIPS), 2011
852011
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
832018
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
812021
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
812009
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
782013
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
772013
Gated recurrent units viewed through the lens of continuous time dynamical systems
ID Jordan, PA Sokol, IM Park
arXiv preprint arXiv:1906.01005, 2019
602019
Bayesian efficient coding
IM Park, JW Pillow
BioRxiv, 178418, 2017
592017
Bayesian and quasi-Bayesian estimators for mutual information from discrete data
E Archer, IM Park, JW Pillow
Entropy 15 (5), 1738-1755, 2013
532013
Metastable dynamics of neural circuits and networks
BAW Brinkman, H Yan, A Maffei, IM Park, A Fontanini, J Wang, ...
Applied Physics Reviews 9 (1), 2022
482022
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