(C: peer-reviewed conferences, J: peer-reviewed journals, *: equal contributions, ^: corresponding authors)
(2025)
[C] Mean-field Games for Continuous Sequence Prediction
Sungwoo Park^, Jaehoon Lee, Honglak Lee, Moontae Lee
Preprint, 2025
[C] Langevin Diffusion Calibrator: Diffusion-based Post-hoc Calibration
Sungwoo Park^, Moontae Lee
Preprint, 2025
(~ 2024)
[C] Mean-field Chaos Diffusion Models
Sungwoo Park, Dongjun Kim, Ahmed M Alaa^
International Conference on Machine Learning (ICML), 2024, Oral presentation (Top 1.5%)
[C] InstructCV: Instruction-Tuned Text-to-Image Diffusion Models as Vision Generalists
Yulu Gan, Sungwoo Park, Alexander Schubert, Anthony Philippakis, Ahmed M Alaa^
International Conference on Learning Representations (ICLR), 2024
[C] Neural Stochastic Differential Games for Time-series Analysis
Sungwoo Park^*, Byoungwoo Park*, Moontae Lee, Changhee Lee
International Conference on Machine Learning (ICML), 2023
[J] SphereGAN: Sphere Generative Adversarial Network Based on Geometric Moment Matching and Its Applications
Sungwoo Park, Junseok Kwon^
IEEE Transaction on Pattern Analysis and Machine Intelligence (TPAMI), 2023
[C] Riemannian Neural SDE: Learning Stochastic Representations on Manifolds
Sungwoo Park, Hyomin Kim, Kyungjae Lee, Junseok Kwon^
Neural Information Processing Systems (NeurIPS), 2022
[C] Neural Markov Controlled SDE: Stochastic Optimization for Continuous-Time Data
Sungwoo Park, Kyungjae Lee, Junseok Kwon^
International Conference on Learning Representations (ICLR), 2022
[J] Riemannian Submanifold Framework for Log-Euclidean Metric Learning on Symmetric Positive Definite Manifolds
Sungwoo Park, Junseok Kwon^
Expert System with Applications, 2022
[C] Wasserstein Distributional Normalization For Robust Distributional Certification of Noisy Labeled Data
Sungwoo Park, Junseok Kwon^
International Conference on Machine Learning (ICML), 2021
[C] Generative Adversarial Networks for Markovian Temporal Dynamics: Stochastic Continuous Data Generation
Sungwoo Park, Dong Wook Shu, Junseok Kwon^
International Conference on Machine Learning (ICML), 2021
[J] Pixel-wise Wasserstein Autoencoder for Highly Generative Dehazing
Guisik Kim, Sungwoo Park, Junseok Kwon^
IEEE Transaction on Image Processing (TIP), 2021
[C] Deep Diffusion-Invariant Wasserstein Distributional Classification
Sungwoo Park, Dong Wook Shu, Junseok Kwon^
Neural Information Processing Systems (NeurIPS), 2020
[C] 3D Point Cloud Generative Adversarial Network Based on Tree Structured Graph Convolutions
Dong Wook Shu*, Sungwoo Park*, Junseok Kwon^
International Conference of Computer Vision (ICCV), 2019
[C] Sphere Generative Adversarial Network Based on Geometric Moment Matching
Sungwoo Park, Junseok Kwon^
Computer Vision and Pattern Recognition (CVPR), 2019, Oral presentation (Top 5%)