← Authors

Mijung Park

15 papers · 2011–2025 · 4 conferences · across top CS/AI conferences

Achievements

🌈 Renaissance Researcher (6) πŸ—ΊοΈ Taxonomy Completionist (32) 🧭 Keyword Pioneer πŸŒ‰ Interdisciplinary Bridge 🌍 Conference Polyglot (4) πŸƒ Academic Marathon (14) 🐣 Hot Topic Early Bird 🐝 Cross-Pollinator (15) πŸ† Keyword Champion (2) πŸ—ƒοΈ Keyword Collector (85) πŸ’Ž Century Club (15) πŸ”₯ Unstoppable (7) πŸ“ˆ Trend Setter

Conferences

AISTATS (6) NIPS (6) AAAI (2) IJCAI (1)

Top co-authors

Jonathan W Pillow (4) Kamil Adamczewski (3) Max Welling (2) Jonathan W. Pillow (2) Wittawat Jitkrittum (2) Frederik Harder (2) Kamalika Choudhary (1) Jongwoo Ko (1) Oluwasanmi Koyejo (1) Anqi Wu (1)

Research topics

Differential Privacy (2)

Keywords

bayesian inference (9) variational inference (6) differential privacy (4) hierarchical model (3) active learning (2) gaussian process (2) receptive field (2) model compression (2) probabilistic modeling (2) moments accountant (2) hierarchical prior (2) posterior distribution (2) markov chain monte carlo (1) synthetic data generation (1) privacy-preserving learning (1) expectation maximization (1) manifold learning (1) feature selection (1) structure learning (1) laplace approximation (1)

Papers

Bayesian Principles Improve Prompt Learning In Vision-Language Models AISTATS 2025
DP-MERF: Differentially Private Mean Embeddings with RandomFeatures for Practical Privacy-preserving Data Generation AISTATS 2021
Dirichlet Pruning for Convolutional Neural Networks AISTATS 2021
Variational Bayes in Private Settings (VIPS) (Extended Abstract) IJCAI 2020
Interpretable and Differentially Private Predictions AAAI 2020
Radial and Directional Posteriors for Bayesian Deep Learning AAAI 2020
DP-EM: Differentially Private Expectation Maximization AISTATS 2017
K2-ABC: Approximate Bayesian Computation with Kernel Embeddings AISTATS 2016
Bayesian Manifold Learning: The Locally Linear Latent Variable Model (LL-LVM) NIPS 2015
Unlocking neural population non-stationarities using hierarchical dynamics models NIPS 2015
Sparse Bayesian structure learning with β€œdependent relevance determination” priors NIPS 2014
Bayesian inference for low rank spatiotemporal neural receptive fields NIPS 2013
Bayesian Structure Learning for Functional Neuroimaging AISTATS 2013
Bayesian active learning with localized priors for fast receptive field characterization NIPS 2012
Active learning of neural response functions with Gaussian processes NIPS 2011