Jung-Woo Ha
Jung-Woo Ha
Research Fellow@NAVER AI Lab, Head of Future AI Center@NAVER, Adj. Prof. @HKUST
Verified email at - Homepage
Cited by
Cited by
StarGAN: Unified Generative Adversarial Networks for Multi-Domain Image-to-Image Translation
Y Choi, M Choi, M Kim, JW Ha, S Kim, J Choo
CVPR 2018, 2018
StarGAN v2: Diverse Image Synthesis for Multiple Domains
Y Choi, Y Uh, J Yoo, JW Ha
Proceedings of the IEEE/CVF Conferences on Computer Vision and Pattern …, 2020
Hadamard product for low-rank bilinear pooling
JH Kim, KW On, J Kim, JW Ha, BT Zhang
ICLR 2017, 2017
Dual attention networks for multimodal reasoning and matching
H Nam, JW Ha, J Kim
CVPR 2017, 2017
Overcoming Catastrophic Forgetting by Incremental Moment Matching
SW Lee, JW Kim, JH Jeon, JW Ha, BT Zhang
NIPS 2017, 2017
Multimodal residual learning for visual qa
JH Kim, SW Lee, D Kwak, MO Heo, J Kim, JW Ha, BT Zhang
Advances in Neural Information Processing Systems, 361-369, 2016
Phase-Aware Speech Enhancement with Deep Complex U-Net
HS Choi, J Kim, J Huh, A Kim, JW Ha, K Lee
ICLR 2019 (to appear), 2019
Photorealistic Style Transfer via Wavelet Transforms
J Yoo, Y Uh, S Chun, B Kang, JW Ha
arXiv preprint arXiv:1903.09760 (ICCV 2019), 2019
Rainbow Memory: Continual Learning with a Memory of Diverse Samples
J Bang, H Kim, YJ Yoo, JW Ha, J Choi
arXiv preprint arXiv:2103.17230 (CVPR 2021), 2021
KLUE: Korean Language Understanding Evaluation
S Park, J Moon, S Kim, WI Cho, J Han, J Park, C Song, J Kim, Y Song, ...
arxiv preprinting arXiv:2105.09680 (NeurIPS 2021 Dataset and Benchmark Track), 2021
AdamP: Slowing down the weight norm increase in momentum-based optimizers
B Heo, S Chun, SJ Oh, D Han, S Yun, Y Uh, JW Ha
arXiv preprint arXiv:2006.08217 (ICLR 2021), 2021
DialogWAE: Multimodal Response Generation with Conditional Wasserstein Auto-Encoder
X Gu, K Cho, JW Ha, S Kim
arXiv:1805.12352 (ICLR 2019), 2019
Generating Videos with Dynamics-aware Implicit Generative Adversarial Networks
S Yu, J Tack, S Mo, H Kim, J Kim, JW Ha, J Shin
International Conference on Learning Representations (ICLR 2022), 2022
Nsml: Meet the mlaas platform with a real-world case study
H Kim, M Kim, D Seo, J Kim, H Park, S Park, H Jo, KH Kim, Y Yang, Y Kim, ...
arXiv preprint arXiv:1810.09957, 2018
What Changes Can Large-scale Language Models Bring? Intensive Study on HyperCLOVA: Billions-scale Korean Generative Pretrained Transformers
B Kim, HS Kim, SW Lee, G Lee, D Kwak, DH Jeon, S Park, S Kim, S Kim, ...
arXiv preprint arXiv:2109.04650 (EMNLP 2021), 2021
Reinforcement learning based recommender system using biclustering technique
S Choi, H Ha, U Hwang, C Kim, JW Ha, S Yoon
arXiv preprint arXiv:1801.05532, 2018
DialogBERT: Discourse-Aware Response Generation via Learning to Recover and Rank Utterances
X Gu, KM Yoo, JW Ha
arXiv preprint arXiv:2012.01775 (AAAI 2021), 2021
NSML: A Machine Learning Platform That Enables You to Focus on Your Models
N Sung, M Kim, H Jo, Y Yang, J Kim, L Lausen, Y Kim, G Lee, D Kwak, ...
arXiv:1712.05902,, 2017
Dataset Condensation via Efficient Synthetic-Data Parameterization
JH Kim, J Kim, SJ Oh, S Yun, H Song, J Jeong, JW Ha, HO Song
arXiv preprint arXiv:2205.14959 (ICML 2022), 2022
Self-supervised Auxiliary Learning with Meta-paths for Heterogeneous Graphs
D Hwang, J Park, S Kwon, KM Kim, JW Ha, HJ Kim
arXiv preprint arXiv:2007.08294 (NeurIPS 2020), 2020
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