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ORCIDIl Park 0002
Person information
- affiliation: Stony Brook University, Department of Neurobiology and Behavior, NY, USA
- affiliation (former): University of Texas at Austin, Neural Coding and Computation Lab, TX, USA
Other persons with the same name
- Il Park — disambiguation page
- Il Park 0001 — K hynix Inc., Icheon, South Korea (and 1 more)
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2020 – today
- 2024
[c32]Ayesha Vermani, Matthew Dowling, Hyungju Jeon, Ian D. Jordan, Josue Nassar, Yves Bernaerts, Yuan Zhao, Steven Van Vaerenbergh, Il Memming Park:
Real-Time Machine Learning Strategies for a New Kind of Neuroscience Experiments. EUSIPCO 2024: 1127-1131- [c31]Hyungju Jeon, Il Memming Park:
Quantifying Signal-to-Noise Ratio in Neural Latent Trajectories via Fisher Information. EUSIPCO 2024: 1621-1625 - [c30]Ayesha Vermani, Il Memming Park
, Josue Nassar:
Leveraging Generative Models for Unsupervised Alignment of Neural Time Series Data. ICLR 2024 - [i18]Matthew Dowling, Yuan Zhao, Il Memming Park:
Large-scale variational Gaussian state-space models. CoRR abs/2403.01371 (2024) - [i17]Ábel Ságodi, Guillermo Martín-Sánchez, Piotr A. Sokól, Il Memming Park:
Back to the Continuous Attractor. CoRR abs/2408.00109 (2024) - 2023
- [j19]Yuan Zhao, Josue Nassar, Ian D. Jordan, Mónica F. Bugallo, Il Memming Park:
Streaming Variational Monte Carlo. IEEE Trans. Pattern Anal. Mach. Intell. 45(1): 1150-1161 (2023) - [j18]Iris R. Stone, Yotam Sagiv, Il Memming Park, Jonathan W. Pillow:
Spectral learning of Bernoulli linear dynamical systems models for decision-making. Trans. Mach. Learn. Res. 2023 (2023) - [c29]Matthew Dowling, Yuan Zhao, Il Memming Park:
Real-time variational method for learning neural trajectory and its dynamics. ICLR 2023 - [c28]Matthew Dowling, Yuan Zhao, Il Memming Park:
Linear Time GPs for Inferring Latent Trajectories from Neural Spike Trains. ICML 2023: 8424-8448 - [i16]Iris R. Stone, Yotam Sagiv, Il Memming Park, Jonathan W. Pillow:
Spectral learning of Bernoulli linear dynamical systems models for decision-making. CoRR abs/2303.02060 (2023) - [i15]Matthew Dowling, Yuan Zhao, Il Memming Park:
Real-Time Variational Method for Learning Neural Trajectory and its Dynamics. CoRR abs/2305.11278 (2023) - [i14]Matthew Dowling, Yuan Zhao, Il Memming Park:
Linear Time GPs for Inferring Latent Trajectories from Neural Spike Trains. CoRR abs/2306.01802 (2023) - [i13]Il Memming Park, Ábel Ságodi, Piotr Aleksander Sokól:
Persistent learning signals and working memory without continuous attractors. CoRR abs/2308.12585 (2023) - 2021
- [j17]Ian D. Jordan, Piotr Aleksander Sokól, Il Memming Park:
Gated Recurrent Units Viewed Through the Lens of Continuous Time Dynamical Systems. Frontiers Comput. Neurosci. 15: 678158 (2021) - [c27]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:
Neural Latents Benchmark '21: Evaluating latent variable models of neural population activity. NeurIPS Datasets and Benchmarks 2021 - [i12]Matthew Dowling, Piotr A. Sokól, Il Memming Park:
Hida-Matérn Kernel. CoRR abs/2107.07098 (2021) - [i11]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:
Neural Latents Benchmark '21: Evaluating latent variable models of neural population activity. CoRR abs/2109.04463 (2021) - 2020
- [j16]Ian D. Jordan, Il Memming Park:
Birhythmic Analog Circuit Maze: A Nonlinear Neurostimulation Testbed. Entropy 22(5): 537 (2020) - [j15]Yuan Zhao, Il Memming Park:
Variational Online Learning of Neural Dynamics. Frontiers Comput. Neurosci. 14: 71 (2020) - [j14]Yuan Zhao, Jacob L. Yates, Aaron J. Levi, Alexander C. Huk, Il Memming Park:
Stimulus-choice (mis)alignment in primate area MT. PLoS Comput. Biol. 16(5) (2020) - [c26]Daniel R. Kepple, Daewon Lee, Colin Prepsius, Volkan Isler, Il Memming Park, Daniel D. Lee:
Jointly Learning Visual Motion and Confidence from Local Patches in Event Cameras. ECCV (6) 2020: 500-516 - [c25]Piotr Aleksander Sokól, Il Memming Park:
Information Geometry of Orthogonal Initializations and Training. ICLR 2020 - [c24]Diego M. Arribas, Yuan Zhao, Il Memming Park:
Rescuing neural spike train models from bad MLE. NeurIPS 2020 - [c23]Josue Nassar, Piotr A. Sokól, SueYeon Chung, Kenneth D. Harris, Il Memming Park:
On 1/n neural representation and robustness. NeurIPS 2020 - [i10]Matthew Dowling, Yuan Zhao, Il Memming Park:
Non-parametric generalized linear model. CoRR abs/2009.01362 (2020) - [i9]Diego M. Arribas, Yuan Zhao, Il Memming Park:
Rescuing neural spike train models from bad MLE. CoRR abs/2010.12362 (2020) - [i8]Josue Nassar, Piotr Aleksander Sokól, SueYeon Chung, Kenneth D. Harris, Il Memming Park:
On 1/n neural representation and robustness. CoRR abs/2012.04729 (2020)
2010 – 2019
- 2019
- [j13]David Hocker, Il Memming Park:
Myopic control of neural dynamics. PLoS Comput. Biol. 15(3) (2019) - [c22]Piotr A. Sokól, Ian D. Jordan, Eben Kadile, Il Memming Park:
Adjoint Dynamics of Stable Limit Cycle Neural Networks. ACSSC 2019: 884-887 - [c21]Josue Nassar, Scott W. Linderman, Mónica F. Bugallo, Il Memming Park:
Tree-Structured Recurrent Switching Linear Dynamical Systems for Multi-Scale Modeling. ICLR (Poster) 2019 - [i7]Ian D. Jordan, Piotr Aleksander Sokól, Il Memming Park:
Gated recurrent units viewed through the lens of continuous time dynamical systems. CoRR abs/1906.01005 (2019) - [i6]Yuan Zhao, Josue Nassar, Ian D. Jordan, Mónica F. Bugallo, Il Memming Park:
Streaming Variational Monte Carlo. CoRR abs/1906.01549 (2019) - 2018
- [c20]Josue Nassar, Scott W. Linderman, Yuan Zhao, Mónica F. Bugallo, Il Memming Park:
Learning Structured Neural Dynamics From Single Trial Population Recording. ACSSC 2018: 666-670 - [i5]Piotr A. Sokól, Il Memming Park:
Information Geometry of Orthogonal Initializations and Training. CoRR abs/1810.03785 (2018) - [i4]Josue Nassar, Scott W. Linderman, Mónica F. Bugallo, Il Memming Park:
Tree-Structured Recurrent Switching Linear Dynamical Systems for Multi-Scale Modeling. CoRR abs/1811.12386 (2018) - 2017
- [j12]Yuan Zhao, Il Memming Park:
Variational Latent Gaussian Process for Recovering Single-Trial Dynamics from Population Spike Trains. Neural Comput. 29(5): 1293-1316 (2017) - [c19]David Hocker, Il Memming Park:
Multistep inference for generalized linear spiking models curbs runaway excitation. NER 2017: 613-616 - 2016
- [c18]Yuan Zhao, Il Memming Park:
Interpretable Nonlinear Dynamic Modeling of Neural Trajectories. NIPS 2016: 3333-3341 - 2015
- [c17]Anqi Wu, Il Memming Park, Jonathan W. Pillow:
Convolutional spike-triggered covariance analysis for neural subunit models. NIPS 2015: 793-801 - 2014
- [j11]Evan Archer, Il Memming Park, Jonathan W. Pillow:
Bayesian entropy estimation for countable discrete distributions. J. Mach. Learn. Res. 15(1): 2833-2868 (2014) - [c16]Il Memming Park, Sohan Seth, Steven Van Vaerenbergh:
Probabilistic kernel least mean squares algorithms. ICASSP 2014: 8272-8276 - 2013
- [j10]Evan Archer, Il Memming Park, Jonathan W. Pillow:
Bayesian and Quasi-Bayesian Estimators for Mutual Information from Discrete Data. Entropy 15(5): 1738-1755 (2013) - [j9]Il Memming Park, Sohan Seth, António R. C. Paiva, Lin Li, José C. Príncipe:
Kernel Methods on Spike Train Space for Neuroscience: A Tutorial. IEEE Signal Process. Mag. 30(4): 149-160 (2013) - [c15]Evan Archer, Il Memming Park, Jonathan W. Pillow:
Bayesian entropy estimation for binary spike train data using parametric prior knowledge. NIPS 2013: 1700-1708 - [c14]Il Memming Park, Evan Archer, Nicholas Priebe, Jonathan W. Pillow:
Spectral methods for neural characterization using generalized quadratic models. NIPS 2013: 2454-2462 - [c13]Il Memming Park, Evan Archer, Kenneth W. Latimer, Jonathan W. Pillow:
Universal models for binary spike patterns using centered Dirichlet processes. NIPS 2013: 2463-2471 - [i3]Evan Archer, Il Memming Park, Jonathan W. Pillow:
Bayesian Entropy Estimation for Countable Discrete Distributions. CoRR abs/1302.0328 (2013) - [i2]Il Memming Park, Sohan Seth, Steven Van Vaerenbergh:
Bayesian Extensions of Kernel Least Mean Squares. CoRR abs/1310.5347 (2013) - 2012
- [j8]Il Memming Park, Sohan Seth, Murali Rao, José C. Príncipe:
Strictly Positive-Definite Spike Train Kernels for Point-Process Divergences. Neural Comput. 24(8): 2223-2250 (2012) - [c12]Evan Archer, Il Memming Park, Jonathan W. Pillow:
Bayesian estimation of discrete entropy with mixtures of stick-breaking priors. NIPS 2012: 2024-2032 - [i1]Il Memming Park, Marcel Nassar, Mijung Park:
Active Bayesian Optimization: Minimizing Minimizer Entropy. CoRR abs/1202.2143 (2012) - 2011
- [j7]Sohan Seth, Murali Rao, Il Park, José C. Príncipe:
A Unified Framework for Quadratic Measures of Independence. IEEE Trans. Signal Process. 59(8): 3624-3635 (2011) - [c11]Il Park, Sohan Seth, Murali Rao, José Carlos Príncipe:
Estimation of symmetric chi-square divergence for point processes. ICASSP 2011: 2016-2019 - [c10]Lin Li, Il Memming Park, Sohan Seth, John S. Choi, Joseph T. Francis, Justin C. Sanchez, José C. Príncipe:
An adaptive decoder from spike trains to micro-stimulation using kernel least-mean-squares (KLMS). MLSP 2011: 1-6 - [c9]Il Memming Park, Jonathan W. Pillow:
Bayesian Spike-Triggered Covariance Analysis. NIPS 2011: 1692-1700 - 2010
- [j6]António R. C. Paiva, Il Park, José C. Príncipe:
A comparison of binless spike train measures. Neural Comput. Appl. 19(3): 405-419 (2010) - [c8]Il Park, José C. Príncipe:
Quantification of inter-trial non-stationarity in spike trains from periodically stimulated neural cultures. ICASSP 2010: 5442-5445 - [c7]Sohan Seth, Il Memming Park, Austin J. Brockmeier, Mulugeta Semework, John S. Choi, Joseph T. Francis, José Carlos Príncipe:
A novel family of non-parametric cumulative based divergences for point processes. NIPS 2010: 2119-2127 - [p1]Jian-Wu Xu, Robert Jenssen, António R. C. Paiva, Il Park:
A Reproducing Kernel Hilbert Space Framework for ITL. Information Theoretic Learning 2010: 351-384
2000 – 2009
- 2009
- [j5]Karl P. Dockendorf, Il Park, Ping He, José C. Príncipe, Thomas B. DeMarse:
Liquid state machines and cultured cortical networks: The separation property. Biosyst. 95(2): 90-97 (2009) - [j4]António R. C. Paiva, Il Park, José C. Príncipe:
A Reproducing Kernel Hilbert Space Framework for Spike Train Signal Processing. Neural Comput. 21(2): 424-449 (2009) - [j3]Weifeng Liu, Il Park, José C. Príncipe:
An Information Theoretic Approach of Designing Sparse Kernel Adaptive Filters. IEEE Trans. Neural Networks 20(12): 1950-1961 (2009) - [j2]Weifeng Liu, Il Park, Yiwen Wang, José C. Príncipe:
Extended kernel recursive least squares algorithm. IEEE Trans. Signal Process. 57(10): 3801-3814 (2009) - [c6]Sohan Seth, Il Park, José C. Príncipe:
A new nonparametric measure of conditional independence. ICASSP 2009: 2981-2984 - 2008
- [j1]Jian-Wu Xu, António R. C. Paiva, Il Park, José Carlos Príncipe:
A Reproducing Kernel Hilbert Space Framework for Information-Theoretic Learning. IEEE Trans. Signal Process. 56(12): 5891-5902 (2008) - [c5]Il Park, José Carlos Príncipe:
Correntropy based Granger causality. ICASSP 2008: 3605-3608 - [c4]António R. C. Paiva, Il Park, José C. Príncipe:
Reproducing kernel Hilbert spaces for spike train analysis. ICASSP 2008: 5212-5215 - 2007
- [c3]António R. C. Paiva, Sudhir Rao, Il Park, José C. Príncipe:
Spectral Clustering of Synchronous Spike Trains. IJCNN 2007: 1831-1835 - [c2]Il Park, António R. C. Paiva, José C. Príncipe, John G. Harris:
A Closed Form Solution for Multiple-Input Spike Based Adaptive Filters. IJCNN 2007: 2064-2068 - 2006
- [c1]Il Park, Dongming Xu, Thomas B. DeMarse, José C. Príncipe:
Modeling of Synchronized Burst in Dissociated Cortical Tissue: An Exploration of Parameter Space. IJCNN 2006: 581-586
Coauthor Index
aka: José Carlos Príncipe
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