Scholar
Minyoung Kim
Google Scholar ID: tKpOSMsAAAAJ
Staff Reseach Scientist, Samsung AI Center Cambridge UK
Citations & Impact
Citations
1,008
H-index
12
i10-index
16
Publications
20
Co-authors
21
list available
Contact
Publications
Resume (English only)
Academic Achievements
- - A Unified Framework for Diffusion Bridge Problems: Flow Matching and Schrödinger Matching into One (arXiv, 2025)
- - LIFT: Learning to Fine-tune via Bayesian Parameter Efficient Meta Fine-tuning (ICLR, 2025, Spotlight)
- - Model Diffusion for Certifiable Few-shot Transfer Learning (arXiv, 2025)
- - FedP^2EFT: Federated Learning to Personalize Parameter Efficient Fine-Tuning for Multilingual LLMs (arXiv, 2025)
- - A Stochastic Approach to Bi-Level Optimization for Hyperparameter Optimization and Meta Learning (AAAI, 2025)
- - A Bayesian Approach to Data Point Selection (NeurIPS, 2024, The first two authors equal contribution)
- - A Hierarchical Bayesian Model for Few-Shot Meta Learning (ICLR, 2024, Spotlight)
- - FedL2P: Federated Learning to Personalize (NeurIPS, 2023)
- - BayesTune: Bayesian Sparse Deep Model Fine-tuning (NeurIPS, 2023)
- - BayesDLL: Bayesian Deep Learning Library (arXiv, 2023)
- - Domain Generalisation via Domain Adaptation: An Adversarial Fourier Amplitude Approach (ICLR, 2023)
- - SwAMP: Swapped assignment of multi-modal pairs for cross-modal retrieval (AISTATS, 2023)
- - FedHB: Hierarchical Bayesian Federated Learning (arXiv, 2023)
- - Fisher SAM: Information Geometry and Sharpness Aware Minimisation (ICML, 2022)
- - Pushing the Limits of Simple Pipelines for Practical Few-Shot Learning (CVPR, 2022)
- - Gaussian Process Modeling of Approximate Inference Errors for Variational Autoencoders (CVPR, 2022)
- - Differentiable Expectation-Maximization for Set Representation Learning (ICLR, 2022)
- - Variational Continual Proxy-Anchor for Deep Metric Learning (ICLR, 2022)
Research Experience
- - Staff Research Scientist at Samsung AI Centre, Cambridge, UK (Dec. 2022 ~ Present)
- - Senior Research Scientist at Samsung AI Centre, Cambridge, UK (Mar. 2019 ~ Nov. 2022)
Background
- Research interests include general deep learning, LLM training and sparse fine-tuning, Transformer architecture analysis, meta learning and few-shot learning, Bayesian statistics, graphical models, Bayesian deep learning, Gaussian processes and neural processes, generative models, diffusion models, etc.
