Mijung Park - RankMe

60 papers A* 4A 6B 1Journal 41Unranked 8

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Safety-Guided Flow (SGF): A Unified Framework for Negative Guidance in Safe Generation. CoRR Mingyu Kim, Young-Heon Kim, Mijung Park
2025	A	`conf`	Bayesian Principles Improve Prompt Learning In Vision-Language Models. AISTATS Mingyu Kim, Jongwoo Ko, Mijung Park
2025	J	`jnl`	Bayesian Principles Improve Prompt Learning In Vision-Language Models. CoRR Mingyu Kim, Jongwoo Ko, Mijung Park
2025	J	`jnl`	Data Unlearning Beyond Uniform Forgetting via Diffusion Time and Frequency Selection. CoRR Jinseong Park, Mijung Park
2025	J	`jnl`	Revisiting Bayesian Model Averaging in the Era of Foundation Models. CoRR Mijung Park
2025	J	`jnl`	Training-Free Safe Denoisers for Safe Use of Diffusion Models. CoRR Mingyu Kim, Dongjun Kim, Amman Yusuf, Stefano Ermon, Mijung Park
2024	J	`jnl`	Differentially Private Kernel Inducing Points using features from ScatterNets (DP-KIP-ScatterNet) for Privacy Preserving Data Distillation. Trans. Mach. Learn. Res. Margarita Vinaroz, Mijung Park
2024	J	`jnl`	Differentially Private Latent Diffusion Models. Trans. Mach. Learn. Res. Michael F. Liu, Saiyue Lyu, Margarita Vinaroz, Mijung Park
2024	J	`jnl`	Differentially Private Neural Tangent Kernels (DP-NTK) for Privacy-Preserving Data Generation. J. Artif. Intell. Res. Yi Yang, Kamil Adamczewski, Xiaoxiao Li, Danica J. Sutherland, Mijung Park
2023	J	`jnl`	Differential Privacy Meets Neural Network Pruning. CoRR Kamil Adamczewski, Mijung Park
2023	J	`jnl`	Differentially Private Kernel Inducing Points (DP-KIP) for Privacy-preserving Data Distillation. CoRR Margarita Vinaroz, Mijung Park
2023	J	`jnl`	Differentially Private Latent Diffusion Models. CoRR Saiyue Lyu, Margarita Vinaroz, Michael F. Liu, Mijung Park
2023	J	`jnl`	Differentially Private Neural Tangent Kernels for Privacy-Preserving Data Generation. CoRR Yilin Yang, Kamil Adamczewski, Danica J. Sutherland, Xiaoxiao Li, Mijung Park
2023	J	`jnl`	Pre-Pruning and Gradient-Dropping Improve Differentially Private Image Classification. CoRR Kamil Adamczewski, Yingchen He, Mijung Park
2023	J	`jnl`	Pre-trained Perceptual Features Improve Differentially Private Image Generation. Trans. Mach. Learn. Res. Frederik Harder, Milad Jalali, Danica J. Sutherland, Mijung Park
2023	J	`jnl`	Rapid response nursing triage outcomes for COVID-19: factors associated with patient's participation in triage recommendations. BMC Medical Informatics Decis. Mak. Jyu-Lin Chen, Chen-Xi Lin, Mijung Park, Jerry John Nutor, Rosalind de Lisser, Thomas J. Hoffmann, Hannah J. Kim
2022	J	`jnl`	Differentially Private Data Generation Needs Better Features. CoRR Frederik Harder, Milad Jalali Asadabadi, Danica J. Sutherland, Mijung Park
2022	J	`jnl`	Differentially Private Stochastic Expectation Propagation. Trans. Mach. Learn. Res. Margarita Vinaroz, Mijung Park
2022	A*	`conf`	Hermite Polynomial Features for Private Data Generation. ICML Margarita Vinaroz, Mohammad-Amin Charusaie, Frederik Harder, Kamil Adamczewski, Mijung Park
2021	J	`jnl`	ABCDP: Approximate Bayesian Computation with Differential Privacy. Entropy Mijung Park, Margarita Vinaroz, Wittawat Jitkrittum
2021	A	`conf`	DP-MERF: Differentially Private Mean Embeddings with RandomFeatures for Practical Privacy-preserving Data Generation. AISTATS Frederik Harder, Kamil Adamczewski, Mijung Park
2021	J	`jnl`	DP-SEP! Differentially Private Stochastic Expectation Propagation. CoRR Margarita Vinaroz, Mijung Park
2021	A	`conf`	Dirichlet Pruning for Convolutional Neural Networks. AISTATS Kamil Adamczewski, Mijung Park
2021	J	`jnl`	Polynomial magic! Hermite polynomials for private data generation. CoRR Mijung Park, Margarita Vinaroz, Mohammad-Amin Charusaie, Frederik Harder
2020	J	`jnl`	Differentially Private Mean Embeddings with Random Features (DP-MERF) for Simple & Practical Synthetic Data Generation. CoRR Frederik Harder, Kamil Adamczewski, Mijung Park
2020	J	`jnl`	Dirichlet Pruning for Neural Network Compression. CoRR Kamil Adamczewski, Mijung Park
2020	A*	`conf`	Interpretable and Differentially Private Predictions. AAAI Frederik Harder, Matthias Bauer, Mijung Park
2020	J	`jnl`	Q-FIT: The Quantifiable Feature Importance Technique for Explainable Machine Learning. CoRR Kamil Adamczewski, Frederik Harder, Mijung Park
2020	A*	`conf`	Radial and Directional Posteriors for Bayesian Deep Learning. AAAI ChangYong Oh, Kamil Adamczewski, Mijung Park
2020	J	`jnl`	Variational Bayes In Private Settings (VIPS). J. Artif. Intell. Res. Mijung Park, James R. Foulds, Kamalika Chaudhuri, Max Welling
2020	A*	`conf`	Variational Bayes in Private Settings (VIPS) (Extended Abstract). IJCAI James R. Foulds, Mijung Park, Kamalika Chaudhuri, Max Welling
2019	—	`conf`	A Differentially Private Kernel Two-Sample Test. ECML/PKDD (1) Anant Raj, Ho Chung Leon Law, Dino Sejdinovic, Mijung Park
2019	J	`jnl`	ABCDP: Approximate Bayesian Computation Meets Differential Privacy. CoRR Mijung Park, Wittawat Jitkrittum
2019	J	`jnl`	DP-MAC: The Differentially Private Method of Auxiliary Coordinates for Deep Learning. CoRR Frederik Harder, Jonas Köhler, Max Welling, Mijung Park
2019	J	`jnl`	Interpretable and Differentially Private Predictions. CoRR Frederik Harder, Matthias Bauer, Mijung Park
2019	J	`jnl`	Neuron ranking - an informed way to condense convolutional neural networks architecture. CoRR Kamil Adamczewski, Mijung Park
2019	J	`jnl`	Private Causal Inference using Propensity Scores. CoRR Si Kai Lee, Luigi Gresele, Mijung Park, Krikamol Muandet
2019	J	`jnl`	Radial and Directional Posteriors for Bayesian Neural Networks. CoRR ChangYong Oh, Kamil Adamczewski, Mijung Park
2018	J	`jnl`	A Differentially Private Kernel Two-Sample Test. CoRR Anant Raj, Ho Chung Leon Law, Dino Sejdinovic, Mijung Park
2018	J	`jnl`	Dethroning the Fano Factor: A Flexible, Model-Based Approach to Partitioning Neural Variability. Neural Comput. Adam S. Charles, Mijung Park, J. Patrick Weller, Gregory D. Horwitz, Jonathan W. Pillow
2017	A	`conf`	DP-EM: Differentially Private Expectation Maximization. AISTATS Mijung Park, James R. Foulds, Kamalika Choudhary, Max Welling
2016	J	`jnl`	A note on privacy preserving iteratively reweighted least squares. CoRR Mijung Park, Max Welling
2016	A	`conf`	K2-ABC: Approximate Bayesian Computation with Kernel Embeddings. AISTATS Mijung Park, Wittawat Jitkrittum, Dino Sejdinovic
2016	J	`jnl`	Practical Privacy For Expectation Maximization. CoRR Mijung Park, Jimmy Foulds, Kamalika Chaudhuri, Max Welling
2016	J	`jnl`	Private Topic Modeling. CoRR Mijung Park, James R. Foulds, Kamalika Chaudhuri, Max Welling
2016	J	`jnl`	Variational Bayes In Private Settings (VIPS). CoRR Mijung Park, James R. Foulds, Kamalika Chaudhuri, Max Welling
2015	—	`conf`	Bayesian Manifold Learning: The Locally Linear Latent Variable Model (LL-LVM). NIPS Mijung Park, Wittawat Jitkrittum, Ahmad Qamar, Zoltán Szabó, Lars Buesing, Maneesh Sahani
2015	J	`jnl`	K2-ABC: Approximate Bayesian Computation with Kernel Embeddings. CoRR Mijung Park, Wittawat Jitkrittum, Dino Sejdinovic
2015	—	`conf`	Unlocking neural population non-stationarities using hierarchical dynamics models. NIPS Mijung Park, Gergo Bohner, Jakob H. Macke
2014	J	`jnl`	Bayesian Active Learning of Neural Firing Rate Maps with Transformed Gaussian Process Priors. Neural Comput. Mijung Park, J. Patrick Weller, Gregory D. Horwitz, Jonathan W. Pillow
2014	—	`conf`	Sparse Bayesian structure learning with dependent relevance determination priors. NIPS Anqi Wu, Mijung Park, Oluwasanmi Koyejo, Jonathan W. Pillow
2013	J	`jnl`	Bayesian Active Learning for Drug Combinations. IEEE Trans. Biomed. Eng. Mijung Park, Marcel Nassar, Haris Vikalo
2013	A	`conf`	Bayesian Structure Learning for Functional Neuroimaging. AISTATS Mijung Park, Oluwasanmi Koyejo, Joydeep Ghosh, Russell A. Poldrack, Jonathan W. Pillow
2013	—	`conf`	Bayesian inference for low rank spatiotemporal neural receptive fields. NIPS Mijung Park, Jonathan W. Pillow
2012	J	`jnl`	Active Bayesian Optimization: Minimizing Minimizer Entropy CoRR Il Memming Park, Marcel Nassar, Mijung Park
2012	—	`conf`	Adaptive experimental design for drug combinations. SSP Mijung Park, Marcel Nassar, Brian L. Evans, Haris Vikalo
2012	—	`conf`	Bayesian active learning with localized priors for fast receptive field characterization. NIPS Mijung Park, Jonathan W. Pillow
2011	B	`conf`	A Machine Learning Approach to Link Adaptation for SC-FDE System. GLOBECOM Zrinka Puljiz, Mijung Park, Robert W. Heath Jr.
2011	—	`conf`	Active learning of neural response functions with Gaussian processes. NIPS Mijung Park, Greg Horwitz, Jonathan W. Pillow
2011	J	`jnl`	Receptive Field Inference with Localized Priors. PLoS Comput. Biol. Mijung Park, Jonathan W. Pillow