International Publications
In Machine Learning, top-tier conferences such as NeurIPS, ICML, ICLR, and AAAI are widely recognized for their significance and influence. For instance, according to Google Scholar metrics, NeurIPS and ICLR are ranked as the 7th and 10th most prestigious venues across all academic fields, respectively. Additionally, oral or spotlight presentations at these conferences are highly competitive, with acceptance rates typically below 5%.
2024
Conference
Textual Training for the Hassle-Free Removal of Unwanted Visual Data
Saehyung Lee, Jisoo Mok, Sangha Park, Yongho Shin, Dahuin Jung†, Sungroh Yoon†, in Proceedings of Conference on Neural Information Processing Systems (NeurIPS) (Top Conference), Vancouver, Canada, December 2024. [† corresponding authors]
Efficient Diffusion-Driven Corruption Editor for Test-Time Adaptation
Yeongtak Oh*, Jonghyun Lee*, Jooyoung Choi, Dahuin Jung, Uiwon Hwang†, Sungroh Yoon†, in Proceedings of European Conference on Computer Vision (ECCV) (Top Conference), Milano, Italy, October 2024. [* equal contribution]
Normality Addition via Normality Detection in Industrial Image Anomaly Detection Models
Jihun Yi, Dahuin Jung, Sungroh Yoon, in Proceedings of International Conference on Artificial Intelligence and Pattern Recognition (AIPR), Xiamen, China, September 2024.
Entropy is not Enough for Test-time Adaptation: From the Perspective of Disentangled Factors
Jonghyun Lee*, Dahuin Jung*, Saehyung Lee, Junsung Park, Juhyeon Shin, Uiwon Hwang†, Sungroh Yoon†, in Proceedings of International Conference on Learning Representations (ICLR) (Top Conference), Spotlight (Top 5%), Vienna, Austria, May 2024. [* equal contribution]
Journal
Sample-efficient Adversarial Imitation Learning
Dahuin Jung, Hyungyu Lee, Sungroh Yoon, Journal of Machine Learning Research (JMLR) (Q1), vol. 25, no. 31, January 2024. [A preliminary version appeared in NeurIPS 2022 Workshop on Deep Reinforcement Learning Workshop, New Orleans, USA, December 2022]
arXiv
Disentangled Motion Modeling for Video Frame Interpolation
Jaihyun Lew, Jooyoung Choi, Chaehun Shin, Dahuin Jung*, Sungroh Yoon*, arXiv:2406.17256 [cs.CV], June 2024. [* Corresponding Authors]
2023
Conference
PUCA: Patch-Unshuffle and Channel Attention for Enhanced Self-Supervised Image Denoising
Hyemi Jang, Junsung Park, Dahuin Jung, Jaihyun Lew, Ho Bae*, Sungroh Yoon*, in Proceedings of Conference on Neural Information Processing Systems (NeurIPS) (Top Conference), New Orleans, USA, December 2023. [* Corresponding Authors]
On the Powerfulness of Textual Outliers for Visual OoD Detection
Sangha Park, Jisoo Mok, Dahuin Jung, Saehyung Lee, Sungroh Yoon, in Proceedings of Conference on Neural Information Processing Systems (NeurIPS) (Top Conference), New Orleans, USA, December 2023.
CLeAR: Continual Learning on Algorithmic Reasoning for Human-like Intelligence
Bong Gyun Kang, HyunGi Kim, Dahuin Jung, Sungroh Yoon, in Proceedings of Conference on Neural Information Processing Systems (NeurIPS) (Top Conference), New Orleans, USA, December 2023.
Generating Instance-level Prompts for Rehearsal-free Continual Learning
Dahuin Jung, Dongyoon Han, Jihwan Bang, and Hwanjun Song, in Proceedings of International Conference on Computer Vision (ICCV) (Top Conference), Oral (Top 2%), Paris, France, October 2023.
Probabilistic Concept Bottleneck Models
Eunji Kim, Dahuin Jung, Sangha Park, Siwon Kim, Sungroh Yoon, in Proceedings of International Conference on Machine Learning (ICML) (Top Conference), Honolulu, USA, July 2023.
Improving Visual Prompt Tuning for Self-supervised Vision Transformers
Seungryong Yoo, Eunji Kim, Dahuin Jung, Jungbeom Lee, Sungroh Yoon, in Proceedings of International Conference on Machine Learning (ICML) (Top Conference), Honolulu, USA, July 2023.
New Insights for the Stability-Plasticity Dilemma in Online Continual Learning
Dahuin Jung, Dongjin Lee, Sunwon Hong, Hyemi Jang, Ho Bae*, Sungroh Yoon*, in Proceedings of International Conference on Learning Representations (ICLR) (Top Conference), Kigali, Rwanda, May 2023. [* Corresponding Authors]
Journal
Real-world Prediction of Preclinical Alzheimer’s Disease with a Deep Generative Model
Uiwon Hwang, Sung-Woo Kim, Dahuin Jung, SeungWook Kim, Hyejoo Lee, Sang Won Seo, Joon-Kyung Seong, Sungroh Yoon, Artificial Intelligence in Medicine (Q1), vol. 144, 102654, October 2023.
PixelSteganalysis: Pixel-wise Hidden Information Removal with Low Visual Degradation
Dahuin Jung, Ho Bae, Hyun-Soo Choi, Sungroh Yoon, IEEE Transactions on Dependable and Secure Computing (Q1), vol. 20, no. 1, pp. 331-342, January/February 2023.
arXiv
Diffusion-Stego: Training-free Diffusion Generative Steganography via Message Projection
Daegyu Kim, Chaehun Shin, Jooyoung Choi, Dahuin Jung, Sungroh Yoon, arXiv:2305.18726 [cs.CV], May 2023.
2022
Conference
FedClassAvg: Local representation learning for personalized federated learning on heterogeneous neural networks
Jaehee Jang, Heoneok Ha, Dahuin Jung, Sungroh Yoon, in Proceedings of the 51st International Conference on Parallel Processing (ICPP), article no. 76, pp. 1-10, August 2022.
Confidence Score for Source-Free Unsupervised Domain Adaptation
Jonghyun Lee, Dahuin Jung, Junho Yim, Sungroh Yoon, in Proceedings of International Conference on Machine Learning (ICML) (Top Conference), Baltimore, USA, July 2022.
Stein Latent Optimization for Generative Adversarial Networks
Uiwon Hwang, Heeseung Kim, Dahuin Jung, Hyemi Jang, Hyungyu Lee, Sungroh Yoon, in Proceedings of International Conference on Learning Representations (ICLR) (Top Conference), April 2022.
Journal
Imbalanced Data Classification via Cooperative Interaction between Classifier and Generator
Hyun-Soo Choi, Dahuin Jung, Siwon Kim, Sungroh Yoon, IEEE Transactions on Neural Networks and Learning Systems (Q1), vol. 33, no. 8, August 2022.
2021
arXiv
Security and Privacy Issues in Deep Learning
Ho Bae*, Jaehee Jang*, Dahuin Jung, Hyemi Jang, Heonseok Ha, Sungroh Yoon, arXiv:1807.11655 [cs.CR], March 2021. [* equal contribution]
2020
Conference
AnomiGAN: Generative Adversarial Networks for Anonymizing Private Medical Data
Ho Bae, Dahuin Jung, Hyun-Soo Choi, Sungroh Yoon, in Proceedings of Pacific Symposium on Biocomputing (PSB), vol. 25, pp. 563-574, Hawaii, USA, January 2020.
iCaps: An Interpretable Classifier via Disentangled Capsule Networks
Dahuin Jung, Jonghyun Lee, Jihun Yi, Sungroh Yoon, in Proceedings of European Conference on Computer Vision (ECCV) (Top Conference), Glasgow, UK, August 2020.
2019
Conference
HexaGAN: Generative Adversarial Nets for Real World Classification
Uiwon Hwang, Dahuin Jung, and Sungroh Yoon, in Proceedings of International Conference on Machine Learning (ICML) (Top Conference), Long Beach, CA, USA, June 2019.