Il Park

According to our database, Il Park authored at least 59 papers between 2006 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of three.

2024

Back to the Continuous Attractor.

Ábel Ságodi, Guillermo Martín-Sánchez, Piotr A. Sokól, Il Memming Park

CoRR, 2024

Large-scale variational Gaussian state-space models.

Matthew Dowling, Yuan Zhao, Il Memming Park

CoRR, 2024

Leveraging Generative Models for Unsupervised Alignment of Neural Time Series Data.

Ayesha Vermani, Il Memming Park, Josue Nassar

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Real-Time Machine Learning Strategies for a New Kind of Neuroscience Experiments.

Ayesha Vermani, Matthew Dowling, Hyungju Jeon, Ian D. Jordan, Josue Nassar, Yves Bernaerts, Yuan Zhao, Steven Van Vaerenbergh, Il Memming Park

Proceedings of the 32nd European Signal Processing Conference, 2024

Quantifying Signal-to-Noise Ratio in Neural Latent Trajectories via Fisher Information.

Hyungju Jeon, Il Memming Park

Proceedings of the 32nd European Signal Processing Conference, 2024

2023

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

Iris R. Stone, Yotam Sagiv, Il Memming Park, Jonathan W. Pillow

Trans. Mach. Learn. Res., 2023

Streaming Variational Monte Carlo.

Yuan Zhao, Josue Nassar, Ian D. Jordan, Mónica F. Bugallo, Il Memming Park

IEEE Trans. Pattern Anal. Mach. Intell., 2023

Persistent learning signals and working memory without continuous attractors.

Il Memming Park, Ábel Ságodi, Piotr Aleksander Sokól

CoRR, 2023

Linear Time GPs for Inferring Latent Trajectories from Neural Spike Trains.

Matthew Dowling, Yuan Zhao, Il Memming Park

Proceedings of the International Conference on Machine Learning, 2023

Real-time variational method for learning neural trajectory and its dynamics.

Matthew Dowling, Yuan Zhao, Il Memming Park

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2021

Gated Recurrent Units Viewed Through the Lens of Continuous Time Dynamical Systems.

Ian D. Jordan, Piotr Aleksander Sokól, Il Memming Park

Frontiers Comput. Neurosci., 2021

Hida-Matérn Kernel.

Matthew Dowling, Piotr A. Sokól, Il Memming Park

CoRR, 2021

Neural Latents Benchmark '21: Evaluating latent variable models of neural population activity.

Felix Pei, Joel Ye, David M. Zoltowski, Anqi Wu, Raeed H. Chowdhury, Hansem Sohn, Joseph E. O'Doherty, Krishna V. Shenoy, Matthew T. Kaufman, Mark M. Churchland, Mehrdad Jazayeri, Lee E. Miller, Jonathan W. Pillow, Il Memming Park, Eva L. Dyer, Chethan Pandarinath

Proceedings of the Neural Information Processing Systems Track on Datasets and Benchmarks 1, 2021

2020

Stimulus-choice (mis)alignment in primate area MT.

Yuan Zhao, Jacob L. Yates, Aaron J. Levi, Alexander C. Huk, Il Memming Park

PLoS Comput. Biol., 2020

Variational Online Learning of Neural Dynamics.

Yuan Zhao, Il Memming Park

Frontiers Comput. Neurosci., 2020

Birhythmic Analog Circuit Maze: A Nonlinear Neurostimulation Testbed.

Ian D. Jordan, Il Memming Park

Entropy, 2020

Non-parametric generalized linear model.

Matthew Dowling, Yuan Zhao, Il Memming Park

CoRR, 2020

On 1/n neural representation and robustness.

Josue Nassar, Piotr A. Sokól, SueYeon Chung, Kenneth D. Harris, Il Memming Park

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.

Diego M. Arribas, Yuan Zhao, Il Memming Park

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.

Piotr Aleksander Sokól, Il Memming Park

Proceedings of the 8th International Conference on Learning Representations, 2020

Jointly Learning Visual Motion and Confidence from Local Patches in Event Cameras.

Daniel R. Kepple, Daewon Lee, Colin Prepsius, Volkan Isler, Il Memming Park, Daniel D. Lee

Proceedings of the Computer Vision - ECCV 2020, 2020

2019

Myopic control of neural dynamics.

David Hocker, Il Memming Park

PLoS Comput. Biol., 2019

Tree-Structured Recurrent Switching Linear Dynamical Systems for Multi-Scale Modeling.

Josue Nassar, Scott W. Linderman, Mónica F. Bugallo, Il Memming Park

Proceedings of the 7th International Conference on Learning Representations, 2019

Adjoint Dynamics of Stable Limit Cycle Neural Networks.

Piotr A. Sokól, Ian D. Jordan, Eben Kadile, Il Memming Park

Proceedings of the 53rd Asilomar Conference on Signals, Systems, and Computers, 2019

2018

Learning Structured Neural Dynamics From Single Trial Population Recording.

Josue Nassar, Scott W. Linderman, Yuan Zhao, Mónica F. Bugallo, Il Memming Park

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.

Yuan Zhao, Il Memming Park

Neural Comput., 2017

Multistep inference for generalized linear spiking models curbs runaway excitation.

David Hocker, Il Memming Park

Proceedings of the 8th International IEEE/EMBS Conference on Neural Engineering, 2017

2016

Interpretable Nonlinear Dynamic Modeling of Neural Trajectories.

Yuan Zhao, Il Memming Park

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.

Anqi Wu, Il Memming Park, Jonathan W. Pillow

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.

Evan Archer, Il Memming Park, Jonathan W. Pillow

J. Mach. Learn. Res., 2014

Probabilistic kernel least mean squares algorithms.

Il Memming Park, Sohan Seth, Steven Van Vaerenbergh

Proceedings of the IEEE International Conference on Acoustics, 2014

2013

Kernel Methods on Spike Train Space for Neuroscience: A Tutorial.

Il Memming Park, Sohan Seth, António R. C. Paiva, Lin Li, José C. Príncipe

IEEE Signal Process. Mag., 2013

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

Evan Archer, Il Memming Park, Jonathan W. Pillow

Entropy, 2013

Bayesian Extensions of Kernel Least Mean Squares.

Il Memming Park, Sohan Seth, Steven Van Vaerenbergh

CoRR, 2013

Spectral methods for neural characterization using generalized quadratic models.

Il Memming Park, Evan Archer, Nicholas Priebe, Jonathan W. Pillow

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.

Il Memming Park, Evan Archer, Kenneth W. Latimer, Jonathan W. Pillow

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.

Evan Archer, Il Memming Park, Jonathan W. Pillow

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.

Il Memming Park, Sohan Seth, Murali Rao, José C. Príncipe

Neural Comput., 2012

Active Bayesian Optimization: Minimizing Minimizer Entropy

Il Memming Park, Marcel Nassar, Mijung Park

CoRR, 2012

Bayesian estimation of discrete entropy with mixtures of stick-breaking priors.

Evan Archer, Il Memming Park, Jonathan W. Pillow

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.

Sohan Seth, Murali Rao, Il Park, José C. Príncipe

IEEE Trans. Signal Process., 2011

Bayesian Spike-Triggered Covariance Analysis.

Il Memming Park, Jonathan W. Pillow

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).

Lin Li, Il Memming Park, Sohan Seth, John S. Choi, Joseph T. Francis, Justin C. Sanchez, José C. Príncipe

Proceedings of the 2011 IEEE International Workshop on Machine Learning for Signal Processing, 2011

Estimation of symmetric chi-square divergence for point processes.

Il Park, Sohan Seth, Murali Rao, José Carlos Príncipe

Proceedings of the IEEE International Conference on Acoustics, 2011

2010

A comparison of binless spike train measures.

António R. C. Paiva, Il Park, José C. Príncipe

Neural Comput. Appl., 2010

A novel family of non-parametric cumulative based divergences for point processes.

Sohan Seth, Il Memming Park, Austin J. Brockmeier, Mulugeta Semework, John S. Choi, Joseph T. Francis, José Carlos Príncipe

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.

Il Park, José C. Príncipe

Proceedings of the IEEE International Conference on Acoustics, 2010

A Reproducing Kernel Hilbert Space Framework for ITL.

Jian-Wu Xu, Robert Jenssen, António R. C. Paiva, Il Park

Proceedings of the Information Theoretic Learning, 2010

2009

Extended kernel recursive least squares algorithm.

Weifeng Liu, Il Park, Yiwen Wang, José C. Príncipe

IEEE Trans. Signal Process., 2009

An Information Theoretic Approach of Designing Sparse Kernel Adaptive Filters.

Weifeng Liu, Il Park, José C. Príncipe

IEEE Trans. Neural Networks, 2009

A Reproducing Kernel Hilbert Space Framework for Spike Train Signal Processing.

António R. C. Paiva, Il Park, José C. Príncipe

Neural Comput., 2009

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

Karl P. Dockendorf, Il Park, Ping He, José C. Príncipe, Thomas B. DeMarse

Biosyst., 2009

A new nonparametric measure of conditional independence.

Sohan Seth, Il Park, José C. Príncipe

Proceedings of the IEEE International Conference on Acoustics, 2009

2008

A Reproducing Kernel Hilbert Space Framework for Information-Theoretic Learning.

Jian-Wu Xu, António R. C. Paiva, Il Park, José Carlos Príncipe

IEEE Trans. Signal Process., 2008

Correntropy based Granger causality.

Il Park, José Carlos Príncipe

Proceedings of the IEEE International Conference on Acoustics, 2008

Reproducing kernel Hilbert spaces for spike train analysis.

António R. C. Paiva, Il Park, José C. Príncipe

Proceedings of the IEEE International Conference on Acoustics, 2008

2007

A Closed Form Solution for Multiple-Input Spike Based Adaptive Filters.

Il Park, António R. C. Paiva, José C. Príncipe, John G. Harris

Proceedings of the International Joint Conference on Neural Networks, 2007

Spectral Clustering of Synchronous Spike Trains.

António R. C. Paiva, Sudhir Rao, Il Park, José C. Príncipe

Proceedings of the International Joint Conference on Neural Networks, 2007

2006

Modeling of Synchronized Burst in Dissociated Cortical Tissue: An Exploration of Parameter Space.

Il Park, Dongming Xu, Thomas B. DeMarse, José C. Príncipe

Proceedings of the International Joint Conference on Neural Networks, 2006