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Mijung Park
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K2-ABC: Approximate Bayesian computation with kernel embeddings
M Park, W Jitkrittum, D Sejdinovic
AISTATS 2016 51, 2016
1042016
Receptive field inference with localized priors
M Park, JW Pillow
PLoS Comput Biol 7 (10), e1002219, 2011
1022011
DP-MERF: Differentially Private Mean Embeddings with RandomFeatures for Practical Privacy-preserving Data Generation
F Harder, K Adamczewski, M Park
International Conference on Artificial Intelligence and Statistics, 1819-1827, 2021
732021
DP-EM: Differentially Private Expectation Maximization
M Park, J Foulds, K Chaudhuri, M Welling
AISTATS 2017, 2017
562017
Variational Bayes In Private Settings (VIPS)
M Park, J Foulds, K Chaudhuri, M Welling
JAIR 2020, 2016
55*2016
Dethroning the Fano Factor: a flexible, model-based approach to partitioning neural variability
AS Charles, M Park, JP Weller, GD Horwitz, JW Pillow
Neural computation 30 (4), 1012-1045, 2018
452018
Interpretable and Differentially Private Predictions
F Harder, M Bauer, M Park
AAAI, 2020
442020
Active learning of neural response functions with Gaussian processes
M Park, G Horwitz, J Pillow
Advances in neural information processing systems 24, 2043-2051, 2011
292011
Bayesian Manifold Learning: The Locally Linear Latent Variable Model (LL-LVM)
M Park, W Jitkrittum, A Qamar, Z Szabó, L Buesing, M Sahani
Advances in Neural Information Processing Systems, 154-162, 2015
282015
Adaptive Bayesian methods for closed-loop neurophysiology
JW Pillow, M Park
Closed loop neuroscience, 3-18, 2016
262016
Bayesian active learning of neural firing rate maps with transformed gaussian process priors
M Park, JP Weller, GD Horwitz, JW Pillow
Neural computation 26 (8), 1519-1541, 2014
262014
Bayesian active learning with localized priors for fast receptive field characterization
M Park, JW Pillow
Advances in neural information processing systems, 2348-2356, 2012
252012
Variational Bayesian inference for forecasting hierarchical time series
M Park, M Nassar
ICML Workshop 2014, 2014
242014
Bayesian active learning for drug combinations
M Park, M Nassar, H Vikalo
IEEE Transactions on Biomedical Engineering 60 (11), 3248-3255, 2013
242013
Sparse Bayesian structure learning with “dependent relevance determination” priors
A Wu, M Park, OO Koyejo, JW Pillow
Advances in Neural Information Processing Systems, 1628-1636, 2014
212014
Bayesian inference for low rank spatiotemporal neural receptive fields
M Park, JW Pillow
Advances in Neural Information Processing Systems, 2688-2696, 2013
192013
Pre-trained perceptual features improve differentially private image generation
F Harder, M Jalali, DJ Sutherland, M Park
Transactions on Machine Learning Research, 2023
17*2023
Radial and Directional Posteriors for Bayesian Deep Learning
C Oh, K Adamczewski, M Park
Proceedings of the AAAI Conference on Artificial Intelligence 34 (04), 5298-5305, 2020
17*2020
Private Topic Modeling
M Park, J Foulds, K Chaudhuri, M Welling
NeurIPS Workshop 2016, 2016
152016
Unlocking neural population non-stationarities using hierarchical dynamics models
M Park, G Bohner, JH Macke
Advances in Neural Information Processing Systems, 145-153, 2015
132015
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