| 3d point cloud generative adversarial network based on tree structured graph convolutions DW Shu, SW Park, J Kwon Proceedings of the IEEE/CVF international conference on computer vision …, 2019 | 353 | 2019 |
| Sphere generative adversarial network based on geometric moment matching SW Park, J Kwon Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019 | 47 | 2019 |
| Pixel-wise wasserstein autoencoder for highly generative dehazing G Kim, SW Park, J Kwon IEEE Transactions on Image Processing 30, 5452-5462, 2021 | 42 | 2021 |
| Neural Markov Controlled SDE: Stochastic Optimization for Continuous-Time Data SW Park, K Lee, J Kwon International Conference on Learning Representations (ICLR), 2022 | 31 | 2022 |
| InstructCV: Instruction-Tuned Text-to-Image Diffusion Models as Vision Generalists Y Gan, S Park, A Schubert, A Philippakis, AM Alaa International Conference on Learning Representations (ICLR), 2023 | 16 | 2023 |
| SphereGAN: Sphere generative adversarial network based on geometric moment matching and its applications SW Park, J Kwon IEEE Transactions on Pattern Analysis and Machine Intelligence 44 (3), 1566-1580, 2020 | 16 | 2020 |
| Generative Adversarial Networks for Markovian Temporal Dynamics: Stochastic Continuous Data Generation S Park, DW Shu, J Kwon The 38th International Conference on Machine Learning (ICML), 2021 | 8 | 2021 |
| Wasserstein distributional harvesting for highly dense 3D point clouds DW Shu, SW Park, J Kwon Pattern Recognition 132, 108978, 2022 | 6 | 2022 |
| Riemannian submanifold framework for log-Euclidean metric learning on symmetric positive definite manifolds SW Park, J Kwon Expert Systems with Applications 202, 117270, 2022 | 5 | 2022 |
| Wasserstein Distributional Normalization For Robust Distributional Certification of Noisy Labeled Data S Park, J Kwon The 38th International Conference on Machine Learning (ICML), 2021 | 5 | 2021 |
| Neural Stochastic Differential Games for Time-series Analysis S Park, B Park, M Lee, C Lee The 40th International Conference on Machine Learning (ICML), 2023 | 2 | 2023 |
| Riemannian neural SDE: learning stochastic representations on manifolds SW Park, H Kim, K Lee, J Kwon Advances in Neural Information Processing Systems 35, 1434-1444, 2022 | 2 | 2022 |
| Mean-field Chaos Diffusion Models S Park, D Kim, A Alaa arXiv preprint arXiv:2406.05396, 2024 | | 2024 |
| Self-Augmentation Based on Noise-Robust Probabilistic Model for Noisy Labels BW Park, SW Park, J Kwon IEEE Access 10, 116141-116151, 2022 | | 2022 |
| Deep diffusion-invariant wasserstein distributional classification SW Park, DW Shu, J Kwon Advances in Neural Information Processing Systems 33, 20697-20706, 2020 | | 2020 |
| Wasserstein Distributional Normalization: Nonparametric Stochastic Modeling for Handling Noisy Labels SW Park, J Kwon | | |
Junseok KwonChung-Ang UniversityVerified email at cau.ac.kr