Il Park

Orcid: 0000-0002-4255-7750

Affiliations:
  • Stony Brook University, Department of Neurobiology and Behavior, NY, USA
  • University of Texas at Austin, Neural Coding and Computation Lab, TX, USA (former)


According to our database1, Il Park authored at least 54 papers between 2006 and 2023.

Collaborative distances:

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

Online presence:

On csauthors.net:

Bibliography

2023
Streaming Variational Monte Carlo.
IEEE Trans. Pattern Anal. Mach. Intell., 2023

Persistent learning signals and working memory without continuous attractors.
CoRR, 2023

Spectral learning of Bernoulli linear dynamical systems models for decision-making.
CoRR, 2023

Linear Time GPs for Inferring Latent Trajectories from Neural Spike Trains.
Proceedings of the International Conference on Machine Learning, 2023

Real-time variational method for learning neural trajectory and its dynamics.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

2021
Gated Recurrent Units Viewed Through the Lens of Continuous Time Dynamical Systems.
Frontiers Comput. Neurosci., 2021

Hida-Matérn Kernel.
CoRR, 2021

Neural Latents Benchmark '21: Evaluating latent variable models of neural population activity.
Proceedings of the Neural Information Processing Systems Track on Datasets and Benchmarks 1, 2021

2020
Stimulus-choice (mis)alignment in primate area MT.
PLoS Comput. Biol., 2020

Variational Online Learning of Neural Dynamics.
Frontiers Comput. Neurosci., 2020

Birhythmic Analog Circuit Maze: A Nonlinear Neurostimulation Testbed.
Entropy, 2020

Non-parametric generalized linear model.
CoRR, 2020

On 1/n neural representation and robustness.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Rescuing neural spike train models from bad MLE.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Information Geometry of Orthogonal Initializations and Training.
Proceedings of the 8th International Conference on Learning Representations, 2020

Jointly Learning Visual Motion and Confidence from Local Patches in Event Cameras.
Proceedings of the Computer Vision - ECCV 2020, 2020

2019
Myopic control of neural dynamics.
PLoS Comput. Biol., 2019

Tree-Structured Recurrent Switching Linear Dynamical Systems for Multi-Scale Modeling.
Proceedings of the 7th International Conference on Learning Representations, 2019

Adjoint Dynamics of Stable Limit Cycle Neural Networks.
Proceedings of the 53rd Asilomar Conference on Signals, Systems, and Computers, 2019

2018
Learning Structured Neural Dynamics From Single Trial Population Recording.
Proceedings of the 52nd Asilomar Conference on Signals, Systems, and Computers, 2018

2017
Variational Latent Gaussian Process for Recovering Single-Trial Dynamics from Population Spike Trains.
Neural Comput., 2017

Multistep inference for generalized linear spiking models curbs runaway excitation.
Proceedings of the 8th International IEEE/EMBS Conference on Neural Engineering, 2017

2016
Interpretable Nonlinear Dynamic Modeling of Neural Trajectories.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

2015
Convolutional spike-triggered covariance analysis for neural subunit models.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

2014
Bayesian entropy estimation for countable discrete distributions.
J. Mach. Learn. Res., 2014

Probabilistic kernel least mean squares algorithms.
Proceedings of the IEEE International Conference on Acoustics, 2014

2013
Kernel Methods on Spike Train Space for Neuroscience: A Tutorial.
IEEE Signal Process. Mag., 2013

Bayesian and Quasi-Bayesian Estimators for Mutual Information from Discrete Data.
Entropy, 2013

Bayesian Extensions of Kernel Least Mean Squares.
CoRR, 2013

Spectral methods for neural characterization using generalized quadratic models.
Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

Universal models for binary spike patterns using centered Dirichlet processes.
Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

Bayesian entropy estimation for binary spike train data using parametric prior knowledge.
Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

2012
Strictly Positive-Definite Spike Train Kernels for Point-Process Divergences.
Neural Comput., 2012

Active Bayesian Optimization: Minimizing Minimizer Entropy
CoRR, 2012

Bayesian estimation of discrete entropy with mixtures of stick-breaking priors.
Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012

2011
A Unified Framework for Quadratic Measures of Independence.
IEEE Trans. Signal Process., 2011

Bayesian Spike-Triggered Covariance Analysis.
Proceedings of the Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 12-14 December 2011, 2011

An adaptive decoder from spike trains to micro-stimulation using kernel least-mean-squares (KLMS).
Proceedings of the 2011 IEEE International Workshop on Machine Learning for Signal Processing, 2011

Estimation of symmetric chi-square divergence for point processes.
Proceedings of the IEEE International Conference on Acoustics, 2011

2010
A comparison of binless spike train measures.
Neural Comput. Appl., 2010

A novel family of non-parametric cumulative based divergences for point processes.
Proceedings of the Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 6-9 December 2010, 2010

Quantification of inter-trial non-stationarity in spike trains from periodically stimulated neural cultures.
Proceedings of the IEEE International Conference on Acoustics, 2010

A Reproducing Kernel Hilbert Space Framework for ITL.
Proceedings of the Information Theoretic Learning, 2010

2009
Extended kernel recursive least squares algorithm.
IEEE Trans. Signal Process., 2009

An Information Theoretic Approach of Designing Sparse Kernel Adaptive Filters.
IEEE Trans. Neural Networks, 2009

A Reproducing Kernel Hilbert Space Framework for Spike Train Signal Processing.
Neural Comput., 2009

Liquid state machines and cultured cortical networks: The separation property.
Biosyst., 2009

A new nonparametric measure of conditional independence.
Proceedings of the IEEE International Conference on Acoustics, 2009

2008
A Reproducing Kernel Hilbert Space Framework for Information-Theoretic Learning.
IEEE Trans. Signal Process., 2008

Correntropy based Granger causality.
Proceedings of the IEEE International Conference on Acoustics, 2008

Reproducing kernel Hilbert spaces for spike train analysis.
Proceedings of the IEEE International Conference on Acoustics, 2008

2007
A Closed Form Solution for Multiple-Input Spike Based Adaptive Filters.
Proceedings of the International Joint Conference on Neural Networks, 2007

Spectral Clustering of Synchronous Spike Trains.
Proceedings of the International Joint Conference on Neural Networks, 2007

2006
Modeling of Synchronized Burst in Dissociated Cortical Tissue: An Exploration of Parameter Space.
Proceedings of the International Joint Conference on Neural Networks, 2006


  Loading...