Il Memming Park
Il Memming Park
Group Leader, Champalimaud Research
Verified email at - Homepage
Cited by
Cited by
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
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
Extended kernel recursive least squares algorithm
W Liu, I Park, Y Wang, JC Príncipe
Signal Processing, IEEE Transactions on 57 (10), 3801-3814, 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
Variational latent gaussian process for recovering single-trial dynamics from population spike trains
Y Zhao, IM Park
Neural computation 29 (5), 1293-1316, 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
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
Bayesian entropy estimation for countable discrete distributions
E Archer, IM Park, JW Pillow
The Journal of Machine Learning Research 15 (1), 2833-2868, 2014
A comparison of binless spike train measures
ARC Paiva, I Park, JC Príncipe
Neural computing & applications 19 (3), 405-419, 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
Bayesian Spike-Triggered Covariance Analysis
IM Park, JW Pillow
Advances in neural information processing systems (NIPS), 2011
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
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
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
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
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
Bayesian and quasi-Bayesian estimators for mutual information from discrete data
E Archer, IM Park, JW Pillow
Entropy 15 (5), 1738-1755, 2013
Gated recurrent units viewed through the lens of continuous time dynamical systems
ID Jordan, PA Sokol, IM Park
arXiv preprint arXiv:1906.01005, 2019
Bayesian efficient coding
IM Park, JW Pillow
BioRxiv, 178418, 2017
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
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