Minyoung Kim

10

Papers

1

Total Citations

Papers (10)

A Stochastic Approach to Bi-Level Optimization for Hyperparameter Optimization and Meta Learning

Unsupervised Visual Domain Adaptation: A Deep Max-Margin Gaussian Process Approach

Pushing the Limits of Simple Pipelines for Few-Shot Learning: External Data and Fine-Tuning Make a Difference

Gaussian Process Modeling of Approximate Inference Errors for Variational Autoencoders

Bayes-Factor-VAE: Hierarchical Bayesian Deep Auto-Encoder Models for Factor Disentanglement

Crafting Dynamic Virtual Activities with Advanced Multimodal Models

Recursive Inference for Variational Autoencoders

FedL2P: Federated Learning to Personalize

BayesTune: Bayesian Sparse Deep Model Fine-tuning

Markov Modulated Gaussian Cox Processes for Semi-Stationary Intensity Modeling of Events Data