Kyongmin Yeo - RankMe

32 papers A* 1B 2Journal 28Unranked 1

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Model-free learning of random dynamical system from noisy observations. J. Comput. Phys. Kyongmin Yeo, Hyomin Shin, Heechang Kim, Minseok Choi
2025	J	`jnl`	Adversarial Spatio-Temporal Attention Networks for Epileptic Seizure Forecasting. CoRR Zan Li, Kyongmin Yeo, Wesley M. Gifford, Lara V. Marcuse, Madeline C. Fields, Bülent Yener
2025	J	`jnl`	Quantitative ultrasound augmented with machine learning to assess tissue microstructure during wound healing. Biomed. Signal Process. Control. David Lemonnier, Brandon J. Sumpio, Maxwell Crouse, Ikram Mezghani, Georgios Theocharidis, Margaret A. Jakus, Karen Rayappa, Naoki Abe, Kyongmin Yeo, Tengfei Ma, Samuel K. Sia, Aristidis Veves, Parag V. Chitnis
2025	J	`jnl`	Sparse Sensor Allocation for Inverse Problems of Detecting Sparse Leaking Emission Sources. CoRR Xinchao Liu, Youngdeok Hwang, Dzung Phan, Levente J. Klein, Xiao Liu, Kyongmin Yeo
2025	J	`jnl`	Spatio-Temporal Attention Network for Epileptic Seizure Prediction. CoRR Zan Li, Kyongmin Yeo, Wesley M. Gifford, Lara V. Marcuse, Madeline C. Fields, Bülent Yener
2025	J	`jnl`	Stabilize physics-informed neural networks for stiff differential equations: Re-spacing layer. Comput. Math. Appl. Eunsuh Kim, Heejae Kwon, Sungha Cho, Kyongmin Yeo, Minseok Choi
2024	J	`jnl`	CaloChallenge 2022: A Community Challenge for Fast Calorimeter Simulation. CoRR Claudius Krause, Michele Faucci Giannelli, Gregor Kasieczka, Benjamin Nachman, Dalila Salamani, David Shih, Anna Zaborowska, Oz Amram, Kerstin Borras, Matthew R. Buckley, Erik Buhmann, Thorsten Buss, Renato Paulo Da Costa Cardoso, Anthony L. Caterini, Nadezda Chernyavskaya, Federico A. G. Corchia, Jesse C. Cresswell, Sascha Diefenbacher, Etienne Dreyer, Vijay Ekambaram, Engin Eren, Florian Ernst, Luigi Favaro, Matteo Franchini, Frank Gaede, Eilam Gross, Shih-Chieh Hsu, Kristina Jaruskova, Benno Käch, Jayant Kalagnanam, Raghav Kansal, Taewoo Kim, Dmitrii Kobylianskii, Anatolii Korol, William Korcari, Dirk Krücker, Katja Krüger, Marco Letizia, Shu Li, Qibin Liu, Xiulong Liu, Gabriel Loaiza-Ganem, Thandikire Madula, Peter McKeown, Isabell-A. Melzer-Pellmann, Vinicius Mikuni, Nam Nguyen, Ayodele Ore, Sofia Palacios Schweitzer, Ian Pang, Kevin Pedro, Tilman Plehn, Witold Pokorski, Huilin Qu, Piyush Raikwar, John A. Raine, Humberto Reyes-González, Lorenzo Rinaldi, Brendan Leigh Ross, Moritz A. W. Scham, Simon Schnake, Chase Shimmin, Eli Shlizerman, Nathalie Soybelman, Mudhakar Srivatsa, Kalliopi Tsolaki, Sofia Vallecorsa, Kyongmin Yeo, Rui Zhang
2024	J	`jnl`	Cascading Failure Prediction via Causal Inference. CoRR Shiuli Subhra Ghosh, Anmol Dwivedi, Ali Tajer, Kyongmin Yeo, Wesley M. Gifford
2023	J	`jnl`	A 3D super-resolution of wind fields via physics-informed pixel-wise self-attention generative adversarial network. CoRR Takuya Kurihana, Kyongmin Yeo, Daniela Szwarcman, Bruce Elmegreen, S. Karthik Mukkavilli, Johannes Schmude, Levente J. Klein
2023	J	`jnl`	A Supervised Contrastive Learning Pretrain-Finetune Approach for Time Series. CoRR Trang H. Tran, Lam M. Nguyen, Kyongmin Yeo, Nam Nguyen, Roman Vaculín
2023	J	`jnl`	An End-to-End Time Series Model for Simultaneous Imputation and Forecast. CoRR Trang H. Tran, Lam M. Nguyen, Kyongmin Yeo, Nam Nguyen, Dzung T. Phan, Roman Vaculín, Jayant Kalagnanam
2023	J	`jnl`	Inverse Models for Estimating the Initial Condition of Spatio-Temporal Advection-Diffusion Processes. Technometrics Xiao Liu, Kyongmin Yeo
2022	J	`jnl`	Generative Adversarial Network for Probabilistic Forecast of Random Dynamical Systems. SIAM J. Sci. Comput. Kyongmin Yeo, Zan Li, Wesley M. Gifford
2022	B	`conf`	Multi-task Learning for Source Attribution and Field Reconstruction for Methane Monitoring. IEEE Big Data Arka Daw, Kyongmin Yeo, Anuj Karpatne, Levente J. Klein
2022	J	`jnl`	Multi-task Learning for Source Attribution and Field Reconstruction for Methane Monitoring. CoRR Arka Daw, Kyongmin Yeo, Anuj Karpatne, Levente J. Klein
2022	B	`conf`	Optimal Sensor Placement for Atmospheric Inverse Modelling. IEEE Big Data Xinchao Liu, Kyongmin Yeo, Levente J. Klein, Youngdeok Hwang, Dzung Phan, Xiao Liu
2022	—	`conf`	Super Resolution for Turbulent Flows in 2D: Stabilized Physics Informed Neural Networks. CDC Mykhaylo Zayats, Malgorzata J. Zimon, Kyongmin Yeo, Sergiy Zhuk
2022	J	`jnl`	Super Resolution for Turbulent Flows in 2D: Stabilized Physics Informed Neural Networks. CoRR Mykhaylo Zayats, Malgorzata J. Zimon, Kyongmin Yeo, Sergiy Zhuk
2021	J	`jnl`	Generative Adversarial Network for Probabilistic Forecast of Random Dynamical System. CoRR Kyongmin Yeo, Zan Li, Wesley M. Gifford
2021	J	`jnl`	S3RP: Self-Supervised Super-Resolution and Prediction for Advection-Diffusion Process. CoRR Chulin Wang, Kyongmin Yeo, Xiao Jin, Andrés Codas, Levente J. Klein, Bruce Elmegreen
2021	J	`jnl`	Variational Inference Formulation for a Model-Free Simulation of a Dynamical System with Unknown Parameters by a Recurrent Neural Network. SIAM J. Sci. Comput. Kyongmin Yeo, Dylan E. C. Grullon, Fan-Keng Sun, Duane S. Boning, Jayant R. Kalagnanam
2020	J	`jnl`	Variational inference formulation for a model-free simulation of a dynamical system with unknown parameters by a recurrent neural network. CoRR Kyongmin Yeo, Dylan E. C. Grullon, Fan-Keng Sun, Duane S. Boning, Jayant R. Kalagnanam
2019	J	`jnl`	Bayesian pollution source identification via an inverse physics model. Comput. Stat. Data Anal. Youngdeok Hwang, Hang Joon Kim, Won Chang, Kyongmin Yeo, Yongku Kim
2019	J	`jnl`	Data-driven Reconstruction of Nonlinear Dynamics from Sparse Observation. CoRR Kyongmin Yeo
2019	J	`jnl`	Data-driven reconstruction of nonlinear dynamics from sparse observation. J. Comput. Phys. Kyongmin Yeo
2019	J	`jnl`	Deep learning algorithm for data-driven simulation of noisy dynamical system. J. Comput. Phys. Kyongmin Yeo, Igor Melnyk
2019	J	`jnl`	Short note on the behavior of recurrent neural network for noisy dynamical system. CoRR Kyongmin Yeo
2018	A*	`conf`	DE-RNN: Forecasting the Probability Density Function of Nonlinear Time Series. ICDM Kyongmin Yeo, Igor Melnyk, Nam Nguyen, Eun Kyung Lee
2018	J	`jnl`	Deep learning algorithm for data-driven simulation of noisy dynamical system. CoRR Kyongmin Yeo, Igor Melnyk
2018	J	`jnl`	Development of a spectral source inverse model by using generalized polynomial chaos. CoRR Kyongmin Yeo, Youngdeok Hwang, Xiao Liu, Jayant Kalagnanam
2017	J	`jnl`	Model-free prediction of noisy chaotic time series by deep learning. CoRR Kyongmin Yeo
2010	J	`jnl`	Simulation of concentrated suspensions using the force-coupling method. J. Comput. Phys. Kyongmin Yeo, Martin R. Maxey