no code implementations • 24 Apr 2024 • TaeYoung Kim, Youngsoo Ha, Myungjoo Kang
Magnetohydrodynamics (MHD) plays a pivotal role in describing the dynamics of plasma and conductive fluids, essential for understanding phenomena such as the structure and evolution of stars and galaxies, and in nuclear fusion for plasma motion through ideal MHD equations.
no code implementations • 23 Apr 2024 • Hoin Jung, Hyunsoo Cho, Myungje Choi, Joowon Lee, Jung Ho Park, Myungjoo Kang
When it comes to a personalized item recommendation system, It is essential to extract users' preferences and purchasing patterns.
no code implementations • 8 Feb 2024 • Jaemoo Choi, Jaewoong Choi, Myungjoo Kang
In this regard, previous WGF models employ the JKO scheme and parametrize transport map for each JKO step.
no code implementations • 31 Jan 2024 • Kyungsung Lee, DongGyu Lee, Myungjoo Kang
We comprehensively evaluate the performance of our model on a variety of noisy inverse problems, including inpainting, denoising, and super-resolution.
no code implementations • 3 Jan 2024 • TaeYoung Kim, Myungjoo Kang
To this end, we developed loss functions inspired by established numerical schemes related to conservation laws and approximated numerical fluxes using Fourier neural operators (FNOs).
1 code implementation • NeurIPS 2023 • Yesom Park, Taekyung Lee, Jooyoung Hahn, Myungjoo Kang
For efficient training, we develop a variable splitting structure by introducing a gradient of the SDF as an auxiliary variable and impose the $p$-Poisson equation directly on the auxiliary variable as a hard constraint.
no code implementations • 24 Oct 2023 • Gregory Holste, Yiliang Zhou, Song Wang, Ajay Jaiswal, Mingquan Lin, Sherry Zhuge, Yuzhe Yang, Dongkyun Kim, Trong-Hieu Nguyen-Mau, Minh-Triet Tran, Jaehyup Jeong, Wongi Park, Jongbin Ryu, Feng Hong, Arsh Verma, Yosuke Yamagishi, Changhyun Kim, Hyeryeong Seo, Myungjoo Kang, Leo Anthony Celi, Zhiyong Lu, Ronald M. Summers, George Shih, Zhangyang Wang, Yifan Peng
Many real-world image recognition problems, such as diagnostic medical imaging exams, are "long-tailed" $\unicode{x2013}$ there are a few common findings followed by many more relatively rare conditions.
no code implementations • 4 Oct 2023 • Jaemoo Choi, Jaewoong Choi, Myungjoo Kang
In this paper, we begin by unifying these OT-based adversarial methods within a single framework.
no code implementations • 7 Jul 2023 • Jaeheyoung Jeon, Jung Hyun Ryu, Jewoong Cho, Myungjoo Kang
This paper presents a solution to the challenges faced by contrastive learning in sequential recommendation systems.
1 code implementation • 24 May 2023 • Joonhun Lee, Myeongho Jeon, Myungjoo Kang, Kyunghyun Park
We propose Feature-aligned N-BEATS as a domain-generalized time series forecasting model.
1 code implementation • NeurIPS 2023 • Jaemoo Choi, Jaewoong Choi, Myungjoo Kang
In this paper, we propose a novel generative model based on the semi-dual formulation of Unbalanced Optimal Transport (UOT).
1 code implementation • 8 May 2023 • Yungi Jeong, Eunseok Yang, Jung Hyun Ryu, Imseong Park, Myungjoo Kang
Mechanical defects in real situations affect observation values and cause abnormalities in multivariate time series, such as sensor values or network data.
1 code implementation • 20 Feb 2023 • Jaemoo Choi, Yesom Park, Myungjoo Kang
Also, we propose a multi-scale training, which improves the performance compared to the diffusion process, by taking advantage of the flexibility of the forward process.
no code implementations • 2 Feb 2023 • Yesom Park, Jaemoo Choi, Changyeon Yoon, Chang hoon Song, Myungjoo Kang
Learning underlying dynamics from data is important and challenging in many real-world scenarios.
no code implementations • ICCV 2023 • Myeongho Jeon, Myungjoo Kang, Joonseok Lee
Instead of assuming and fixing the target distribution at training, our proposed approach allows adjusting the feature space the model refers to at every prediction, i. e., instance-wise adaptive inference.
no code implementations • 25 Nov 2022 • Chang hoon Song, Geonho Hwang, Jun Ho Lee, Myungjoo Kang
In this study, we prove the universality of deep narrow RNNs and show that the upper bound of the minimum width for universality can be independent of the length of the data.
no code implementations • 18 Nov 2022 • Geonho Hwang, Myungjoo Kang
Despite its widespread adoption, our understanding of its universal approximation properties has been limited due to its intricate nature.
no code implementations • 11 Oct 2022 • Jaewoong Choi, Geonho Hwang, Hyunsoo Cho, Myungjoo Kang
This semantic basis represents sample-independent meaningful perturbations that change the same semantic attribute of an image on the entire latent space.
no code implementations • 12 Sep 2022 • TaeYoung Kim, Myungjoo Kang
Using capacity based on these norms, we bound the generalization error of the model.
no code implementations • 11 Aug 2022 • Hyoje Lee, Yeachan Park, Hyun Seo, Myungjoo Kang
In this paper, we propose a simple and effective self-knowledge distillation method using a dropout (SD-Dropout).
no code implementations • 26 May 2022 • Jaewoong Choi, Geonho Hwang, Hyunsoo Cho, Myungjoo Kang
In this paper, we approach this problem through a geometric analysis of latent spaces as a manifold.
1 code implementation • CVPR 2022 • Myeongho Jeon, Daekyung Kim, Woochul Lee, Myungjoo Kang, Joonseok Lee
Although convolutional neural networks (CNNs) achieve state-of-the-art in image classification, recent works address their unreliable predictions due to their excessive dependence on biased training data.
1 code implementation • 15 Jun 2021 • Jaemoo Choi, Changyeon Yoon, Jeongwoo Bae, Myungjoo Kang
Deep probabilistic generative models facilitate OOD detection by estimating the likelihood of a data sample.
Out-of-Distribution Detection Out of Distribution (OOD) Detection
2 code implementations • ICLR 2022 • Jaewoong Choi, Junho Lee, Changyeon Yoon, Jung Ho Park, Geonho Hwang, Myungjoo Kang
The global warpage implies that the latent space is not well-aligned globally and therefore the global traversal directions are bound to show limited success on it.
no code implementations • 25 May 2021 • Hyungmin Roh, Myungjoo Kang
In this paper, we introduce a novel deep neural network suitable for multi-scale analysis and propose efficient model-agnostic methods that help the network extract information from high-frequency domains to reconstruct clearer images.
no code implementations • 7 Jan 2021 • Sungkwon An, Jeonghoon Kim, Myungjoo Kang, Shahbaz Razaei, Xin Liu
Specifically, we employ orthogonal low-rank embedding in the latent space to disentangle the features in the latent space using mutual class information.
1 code implementation • 29 Sep 2020 • Yeachan Park, Myeongho Jeon, Junho Lee, Myungjoo Kang
Experimental results on both synthetic and real-world rainy datasets demonstrate that the proposed model significantly outperforms existing state-of-the-art models.
Ranked #1 on Single Image Deraining on RainCityscapes
no code implementations • 17 Sep 2020 • Jaewoong Choi, Geonho Hwang, Myungjoo Kang
To represent these generative factors of data, we introduce two sets of continuous latent variables, private variable and public variable.
no code implementations • 9 Jul 2020 • Sungkwon An, Hyungmin Roh, Myungjoo Kang
Subsequently, we propose a deblurring network that restores sharp images using the estimated blur kernel.
1 code implementation • 8 May 2020 • Abdelrahman Abdelhamed, Mahmoud Afifi, Radu Timofte, Michael S. Brown, Yue Cao, Zhilu Zhang, WangMeng Zuo, Xiaoling Zhang, Jiye Liu, Wendong Chen, Changyuan Wen, Meng Liu, Shuailin Lv, Yunchao Zhang, Zhihong Pan, Baopu Li, Teng Xi, Yanwen Fan, Xiyu Yu, Gang Zhang, Jingtuo Liu, Junyu Han, Errui Ding, Songhyun Yu, Bumjun Park, Jechang Jeong, Shuai Liu, Ziyao Zong, Nan Nan, Chenghua Li, Zengli Yang, Long Bao, Shuangquan Wang, Dongwoon Bai, Jungwon Lee, Youngjung Kim, Kyeongha Rho, Changyeop Shin, Sungho Kim, Pengliang Tang, Yiyun Zhao, Yuqian Zhou, Yuchen Fan, Thomas Huang, Zhihao LI, Nisarg A. Shah, Wei Liu, Qiong Yan, Yuzhi Zhao, Marcin Możejko, Tomasz Latkowski, Lukasz Treszczotko, Michał Szafraniuk, Krzysztof Trojanowski, Yanhong Wu, Pablo Navarrete Michelini, Fengshuo Hu, Yunhua Lu, Sujin Kim, Wonjin Kim, Jaayeon Lee, Jang-Hwan Choi, Magauiya Zhussip, Azamat Khassenov, Jong Hyun Kim, Hwechul Cho, Priya Kansal, Sabari Nathan, Zhangyu Ye, Xiwen Lu, Yaqi Wu, Jiangxin Yang, Yanlong Cao, Siliang Tang, Yanpeng Cao, Matteo Maggioni, Ioannis Marras, Thomas Tanay, Gregory Slabaugh, Youliang Yan, Myungjoo Kang, Han-Soo Choi, Kyungmin Song, Shusong Xu, Xiaomu Lu, Tingniao Wang, Chunxia Lei, Bin Liu, Rajat Gupta, Vineet Kumar
This challenge is based on a newly collected validation and testing image datasets, and hence, named SIDD+.
1 code implementation • 12 Jan 2020 • Yeachan Park, Myungjoo Kang
Machine learning models can leak information regarding the dataset they have trained.
2 code implementations • 3 Jul 2019 • Jaewoong Choi, Hyun Seo, Suii Im, Myungjoo Kang
We replace the dynamic routing and squash activation function of the capsule network with dynamic routing (CapsuleNet) with the attention routing and capsule activation.
no code implementations • 28 Feb 2019 • Sangyeon Kim, Myungjoo Kang
In recent times, deep learning methods (especially time series analysis) have performed outstandingly for various industrial problems, with better prediction than machine learning methods.