Stochastic approach on a simplified OCC model for uncertainty and believability. - Won Hwa Kim; Jeong Woo Park; Won Hyong Lee; Woo Hyun Kim; Myung Jin Chung (CIRA, 2009)

Synchronized multimodal expression generation using editing toolkit for a human-friendly robot. - Woo Hyun Kim; Jeong Woo Park; Won Hyong Lee; Won Hwa Kim; Myung Jin Chung (ROBIO, 2009)

Lifelike facial expression of mascot-type robot based on emotional boundaries. - Jeong Woo Park; Woo Hyun Kim; Won Hyong Lee; Won Hwa Kim; Myung Jin Chung (ROBIO, 2009)

Wavelet based multi-scale shape features on arbitrary surfaces for cortical thickness discrimination. - Won Hwa Kim; Deepti Pachauri; Charles R. Hatt; Moo K. Chung; Sterling C. Johnson; Vikas Singh (NIPS, 2012)

Multi-resolution Shape Analysis via Non-Euclidean Wavelets: Applications to Mesh Segmentation and Surface Alignment Problems. - Won Hwa Kim; Moo K. Chung; Vikas Singh (CVPR, 2013)

Multi-resolutional Brain Network Filtering and Analysis via Wavelets on Non-Euclidean Space. - Won Hwa Kim; Nagesh Adluru; Moo K. Chung; Sylvia Charchut; Johnson J. GadElkarim; Lori L. Altshuler; Teena Moody; Anand R. Kumar; Vikas Singh; Alex D. Leow (MICCAI (3), 2013)

Evaluation of Ultrasound Synthetic Aperture Imaging Using Bidirectional Pixel-Based Focusing: Preliminary Phantom and In Vivo Breast Study. - Choye Kim; Changhan Yoon; Jong-Ho Park; Yuhwa Lee; Won Hwa Kim; Jung Min Chang; Byung Ihn Choi; Tai-Kyong Song; Yang-Mo Yoo (IEEE Trans. Biomed. Eng., 2013)

The 4D Hyperspherical Diffusion Wavelet: A New Method for the Detection of Localized Anatomical Variation. - Ameer Pasha Hosseinbor; Won Hwa Kim; Nagesh Adluru; Amit Acharya; Houri K. Vorperian; Moo K. Chung (MICCAI (3), 2014)

Multi-resolutional shape features via non-Euclidean wavelets: Applications to statistical analysis of cortical thickness. - Won Hwa Kim; Vikas Singh; Moo K. Chung; Chris Hinrichs; Deepti Pachauri; Ozioma C. Okonkwo; Sterling C. Johnson (NeuroImage, 2014)

Statistical inference models for image datasets with systematic variations. - Won Hwa Kim; Barbara B. Bendlin; Moo K. Chung; Sterling C. Johnson; Vikas Singh (CVPR, 2015)

On Statistical Analysis of Neuroimages with Imperfect Registration. - Won Hwa Kim; Sathya N. Ravi; Sterling C. Johnson; Ozioma C. Okonkwo; Vikas Singh (ICCV, 2015)

Multi-resolution statistical analysis on graph structured data in neuroimaging. - Won Hwa Kim; Vikas Singh; Moo K. Chung; Nagesh Adluru; Barbara B. Bendlin; Sterling C. Johnson (ISBI, 2015)

Multi-resolution statistical analysis of brain connectivity graphs in preclinical Alzheimer's disease. - Won Hwa Kim; Nagesh Adluru; Moo K. Chung; Ozioma C. Okonkwo; Sterling C. Johnson; Barbara B. Bendlin; Vikas Singh (NeuroImage, 2015)

Latent Variable Graphical Model Selection Using Harmonic Analysis: Applications to the Human Connectome Project (HCP). - Won Hwa Kim; Hyunwoo J. Kim; Nagesh Adluru; Vikas Singh (CVPR, 2016)

Adaptive Signal Recovery on Graphs via Harmonic Analysis for Experimental Design in Neuroimaging. - Won Hwa Kim; Seong Jae Hwang; Nagesh Adluru; Sterling C. Johnson; Vikas Singh (ECCV (6), 2016)

Online Graph Completion: Multivariate Signal Recovery in Computer Vision. - Won Hwa Kim; Mona Jalal; Seong Jae Hwang; Sterling C. Johnson; Vikas Singh (CVPR, 2017)

Conditional Recurrent Flow: Conditional Generation of Longitudinal Samples With Applications to Neuroimaging. - Seong Jae Hwang; Zirui Tao; Vikas Singh; Won Hwa Kim (ICCV, 2019)

Associations Between Positron Emission Tomography Amyloid Pathology and Diffusion Tensor Imaging Brain Connectivity in Pre-Clinical Alzheimer's Disease. - Seong Jae Hwang; Nagesh Adluru; Won Hwa Kim; Sterling C. Johnson; Barbara B. Bendlin; Vikas Singh (Brain Connect., 2019)

Multi-resolution Graph Neural Network for Identifying Disease-specific Variations in Brain Connectivity. - Xin Ma 006; Guorong Wu 001; Won Hwa Kim (CoRR, 2019)

Enriching Statistical Inferences on Brain Connectivity for Alzheimer's Disease Analysis via Latent Space Graph Embedding. - Xin Ma 006; Guorong Wu 001; Won Hwa Kim (ISBI, 2020)

Weakly-supervised US breast tumor characterization and localization with a box convolution network. - Chanho Kim; Won Hwa Kim; Hye Jung Kim; Jaeil Kim (Computer-Aided Diagnosis, 2020)

COVLET: Covariance-Based Wavelet-Like Transform for Statistical Analysis of Brain Characteristics in Children. - Fan Yang; Amal Isaiah; Won Hwa Kim (MICCAI (7), 2020)

Toward Unbiased Facial Expression Recognition in the Wild via Cross-Dataset Adaptation. - ByungOk Han; Woo-han Yun; Jang-Hee Yoo; Won Hwa Kim (IEEE Access, 2020)

BrainNET: Inference of Brain Network Topology Using Machine Learning. - Gowtham Krishnan Murugesan; Chandan Ganesh Bangalore Yogananda; Sahil S. Nalawade; Elizabeth M. Davenport; Benjamin C. Wagner; Won Hwa Kim; Joseph A. Maldjian (Brain Connect., 2020)

Learning Multi-resolution Graph Edge Embedding for Discovering Brain Network Dysfunction in Neurological Disorders. - Xin Ma 006; Guorong Wu 001; Seong Jae Hwang; Won Hwa Kim (IPMI, 2021)

Covariate Correcting Networks for Identifying Associations Between Socioeconomic Factors and Brain Outcomes in Children. - Hyuna Cho; Gunwoong Park; Amal Isaiah; Won Hwa Kim (MICCAI (7), 2021)

A Multi-scale Capsule Network for Improving Diagnostic Generalizability in Breast Cancer Diagnosis Using Ultrasonography. - Chanho Kim; Won Hwa Kim; Hye Jung Kim; Jaeil Kim (PRIME@MICCAI, 2021)

Prediction of Pathological Complete Response to Neoadjuvant Chemotherapy Using Multi-scale Patch Learning with Mammography. - Ho Kyung Shin; Won Hwa Kim; Hye Jung Kim; Chanho Kim; Jaeil Kim (PRIME@MICCAI, 2021)

Disentangled Sequential Graph Autoencoder for Preclinical Alzheimer's Disease Characterizations from ADNI Study. - Fan Yang; Rui Meng; Hyuna Cho; Guorong Wu 001; Won Hwa Kim (MICCAI (2), 2021)

Very Compact Clusters with Structural Regularization via Similarity and Connectivity. - Xin Ma 006; Won Hwa Kim (CoRR, 2021)

Locally Normalized Soft Contrastive Clustering for Compact Clusters. - Xin Ma 006; Won Hwa Kim (IJCAI, 2022)

Disentangled Representation of Longitudinal Β-Amyloid for AD Via Sequential Graph Variational Autoencoder with Supervision. - Fan Yang; Guorong Wu 001; Won Hwa Kim (ISBI, 2022)

How Much to Aggregate: Learning Adaptive Node-Wise Scales on Graphs for Brain Networks. - Injun Choi; Guorong Wu 001; Won Hwa Kim (MICCAI (1), 2022)

Neuro-RDM: An Explainable Neural Network Landscape of Reaction-Diffusion Model for Cognitive Task Recognition. - Tingting Dan; Hongmin Cai; Zhuobin Huang; Paul J. Laurienti; Won Hwa Kim; Guorong Wu 001 (MICCAI (8), 2022)

What Do Untargeted Adversarial Examples Reveal in Medical Image Segmentation? - Gangin Park; Chunsan Hong; Bohyung Kim; Won Hwa Kim (UNSURE@MICCAI, 2022)

Performing Group Difference Testing on Graph Structured Data From GANs: Analysis and Applications in Neuroimaging. - Tuan Q. Dinh; Yunyang Xiong; Zhichun Huang; Tien Vo; Akshay Mishra; Won Hwa Kim; Sathya N. Ravi; Vikas Singh (IEEE Trans. Pattern Anal. Mach. Intell., 2022)

A Case Study of Quantizing Convolutional Neural Networks for Fast Disease Diagnosis on Portable Medical Devices. - Mukhammed Garifulla; Juncheol Shin; Chanho Kim; Won Hwa Kim; Hye Jung Kim; Jaeil Kim; Seokin Hong (Sensors, 2022)

Devil's on the Edges: Selective Quad Attention for Scene Graph Generation. - Deunsol Jung; Sanghyun Kim; Won Hwa Kim; Minsu Cho (CVPR, 2023)

Learning to Boost Training by Periodic Nowcasting Near Future Weights. - Jinhyeok Jang; Woo-han Yun; Won Hwa Kim; Youngwoo Yoon; Jaehong Kim 001; Jaeyeon Lee 001; ByungOk Han (ICML, 2023)

HoloBrain: A Harmonic Holography for Self-organized Brain Function. - Huan Liu 017; Tingting Dan; Zhuobin Huang; Defu Yang; Won Hwa Kim; Minjeong Kim; Paul J. Laurienti; Guorong Wu 001 (IPMI, 2023)

Learning Covariance-Based Multi-Scale Representation of Neuroimaging Measures for Alzheimer Classification. - Seunghun Baek; Injun Choi; Mustafa Dere; Minjeong Kim; Guorong Wu 001; Won Hwa Kim (ISBI, 2023)

Anti-adversarial Consistency Regularization for Data Augmentation: Applications to Robust Medical Image Segmentation. - Hyuna Cho; Yubin Han; Won Hwa Kim (MICCAI (4), 2023)

Mixing Temporal Graphs with MLP for Longitudinal Brain Connectome Analysis. - Hyuna Cho; Guorong Wu 001; Won Hwa Kim (MICCAI (2), 2023)

Enhance Early Diagnosis Accuracy of Alzheimer's Disease by Elucidating Interactions Between Amyloid Cascade and Tau Propagation. - Tingting Dan; Minjeong Kim; Won Hwa Kim; Guorong Wu 001 (MICCAI (3), 2023)

TauFlowNet: Uncovering Propagation Mechanism of Tau Aggregates by Neural Transport Equation. - Tingting Dan; Minjeong Kim; Won Hwa Kim; Guorong Wu 001 (MICCAI (3), 2023)

Uncovering Structural-Functional Coupling Alterations for Neurodegenerative Diseases. - Tingting Dan; Minjeong Kim; Won Hwa Kim; Guorong Wu 001 (MICCAI (3), 2023)

RESToring Clarity: Unpaired Retina Image Enhancement Using Scattering Transform. - Ellen Jieun Oh; Yechan Hwang; Yubin Han; Taegeun Choi; Geunyoung Lee; Won Hwa Kim (MICCAI (10), 2023)

Convolving Directed Graph Edges via Hodge Laplacian for Brain Network Analysis. - Joonhyuk Park; Yechan Hwang; Minjeong Kim; Moo K. Chung; Guorong Wu 001; Won Hwa Kim (MICCAI (5), 2023)

Multi-resolution Spectral Coherence for Graph Generation with Score-based Diffusion. - Hyuna Cho; Minjae Jeong; Sooyeon Jeon; Sungsoo Ahn; Won Hwa Kim (NeurIPS, 2023)

Re-Think and Re-Design Graph Neural Networks in Spaces of Continuous Graph Diffusion Functionals. - Tingting Dan; Jiaqi Ding; Ziquan Wei; Shahar Z. Kovalsky; Minjeong Kim; Won Hwa Kim; Guorong Wu 001 (NeurIPS, 2023)

A Study on the Effectiveness of Deep Learning-Based Anomaly Detection Methods for Breast Ultrasonography. - Changhee Yun; Bomi Eom; Sungjun Park; Chanho Kim; Dohwan Kim; Farah Jabeen; Won Hwa Kim; Hye Jung Kim; Jaeil Kim (Sensors, 2023)

Dynamic covariance estimation via predictive Wishart process with an application on brain connectivity estimation. - Rui Meng; Fan Yang; Won Hwa Kim (Comput. Stat. Data Anal., 2023)

Learning to Approximate Adaptive Kernel Convolution on Graphs. - Jaeyoon Sim; Sooyeon Jeon; Injun Choi; Guorong Wu 001; Won Hwa Kim (AAAI, 2024)

CNG-SFDA: Clean-and-Noisy Region Guided Online-Offline Source-Free Domain Adaptation. - Hyeonwoo Cho; Chanmin Park; Dong-Hee Kim; Jinyoung Kim; Won Hwa Kim (ACCV (8), 2024)

Decoupled Marked Temporal Point Process using Neural Ordinary Differential Equations. - Yujee Song; Donghyun Lee 006; Rui Meng; Won Hwa Kim (ICLR, 2024)

Neurodegenerative Brain Network Classification via Adaptive Diffusion with Temporal Regularization. - Hyuna Cho; Jaeyoon Sim; Guorong Wu 001; Won Hwa Kim (ICML, 2024)

Exploring the Enigma of Neural Dynamics Through A Scattering-Transform Mixer Landscape for Riemannian Manifold. - Tingting Dan; Ziquan Wei; Won Hwa Kim; Guorong Wu 001 (ICML, 2024)

Modality-Agnostic Style Transfer for Holistic Feature Imputation. - Seunghun Baek; Jaeyoon Sim; Mustafa Dere; Minjeong Kim; Guorong Wu 001; Won Hwa Kim (ISBI, 2024)

OCL: Ordinal Contrastive Learning for Imputating Features with Progressive Labels. - Seunghun Baek; Jaeyoon Sim; Guorong Wu 001; Won Hwa Kim (MICCAI (2), 2024)

Uncovering Cortical Pathways of Prion-Like Pathology Spreading in Alzheimer's Disease by Neural Optimal Mass Transport. - Yanquan Huang; Tingting Dan; Won Hwa Kim; Guorong Wu 001 (MICCAI (2), 2024)

Multi-order Simplex-Based Graph Neural Network for Brain Network Analysis. - Yechan Hwang; Soojin Hwang; Guorong Wu 001; Won Hwa Kim (MICCAI (5), 2024)

Gene-to-Image: Decoding Brain Images from Genetics via Latent Diffusion Models. - Sooyeon Jeon; Yujee Song; Won Hwa Kim (PRIME@MICCAI, 2024)

Uncertainty-Aware Diffusion-Based Adversarial Attack for Realistic Colonoscopy Image Synthesis. - Minjae Jeong; Hyuna Cho; Sungyoon Jung; Won Hwa Kim (MICCAI (9), 2024)

Multi-modal Graph Neural Network with Transformer-Guided Adaptive Diffusion for Preclinical Alzheimer Classification. - Jaeyoon Sim; Minjae Lee; Guorong Wu 001; Won Hwa Kim (MICCAI (5), 2024)

Interactive Network Perturbation between Teacher and Students for Semi-Supervised Semantic Segmentation. - Hyuna Cho; Injun Choi; Suha Kwak; Won Hwa Kim (WACV, 2024)

Style-KD: Class-imbalanced medical image classification via style knowledge distillation. - Inhyuk Park; Won Hwa Kim; Jongbin Ryu (Biomed. Signal Process. Control., 2024)

CNA-TTA: Clean and Noisy Region Aware Feature Learning within Clusters for Online-Offline Test-Time Adaptation. - Hyeonwoo Cho; Chanmin Park; Jinyoung Kim; Won Hwa Kim (CoRR, 2024)

Joint-Embedding Predictive Architecture for Self-Supervised Learning of Mask Classification Architecture. - Dong-Hee Kim; Sungduk Cho; Hyeonwoo Cho; Chanmin Park; Jinyoung Kim; Won Hwa Kim (CoRR, 2024)

Machine Learning on Dynamic Functional Connectivity: Promise, Pitfalls, and Interpretations. - Jiaqi Ding; Tingting Dan; Ziquan Wei; Hyuna Cho; Paul J. Laurienti; Won Hwa Kim; Guorong Wu 001 (CoRR, 2024)

TauFlowNet: Revealing latent propagation mechanism of tau aggregates using deep neural transport equations. - Tingting Dan; Mustafa Dere; Won Hwa Kim; Minjeong Kim; Guorong Wu 001 (Medical Image Anal., 2024)

Developing Explainable Deep Model for Discovering Novel Control Mechanism of Neuro-Dynamics. - Tingting Dan; Minjeong Kim; Won Hwa Kim; Guorong Wu 001 (IEEE Trans. Medical Imaging, 2024)

Improving Sound Source Localization with Joint Slot Attention on Image and Audio. - Inho Kim; Youngkil Song; Jicheol Park; Won Hwa Kim; Suha Kwak (CVPR, 2025)

Conditional Diffusion with Ordinal Regression: Longitudinal Data Generation for Neurodegenerative Disease Studies. - Hyuna Cho; Ziquan Wei; Seungjoo Lee; Tingting Dan; Guorong Wu 001; Won Hwa Kim (ICLR, 2025)

HGM³: Hierarchical Generative Masked Motion Modeling with Hard Token Mining. - Minjae Jeong; Yechan Hwang; Jaejin Lee; Sungyoon Jung; Won Hwa Kim (ICLR, 2025)

Targeted Unlearning Using Perturbed Sign Gradient Methods With Applications On Medical Images. - George R. Nahass; Zhu Wang; Homa Rashidisabet; Won Hwa Kim; Sasha Hubschman; Jeffrey C. Peterson; Ghasem Yazdanpanah; Chad A. Purnell; Pete Setabutr; Ann Q. Tran; Darvin Yi; Sathya N. Ravi (CoRR, 2025)

Is Exchangeability better than I.I.D to handle Data Distribution Shifts while Pooling Data for Data-scarce Medical image segmentation? - Ayush Roy; Samin Enam; Jun Xia; Vishnu Suresh Lokhande; Won Hwa Kim (CoRR, 2025)