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Seong Jae Hwang
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2020 – today
- 2024
- [c21]Kyungsik Lee, Youngmi Jun, Eunji Kim, Suhyun Kim, Seong Jae Hwang, Jonghyun Choi:
Kore Initial Clustering for Unsupervised Domain Adaptation. VISIGRAPP (2): VISAPP 2024: 425-432 - [i20]Chanyoung Kim, Woojung Han, Dayun Ju, Seong Jae Hwang:
EAGLE: Eigen Aggregation Learning for Object-Centric Unsupervised Semantic Segmentation. CoRR abs/2403.01482 (2024) - [i19]Woojung Han, Chanyoung Kim, Dayun Ju, Yumin Shim, Seong Jae Hwang:
Advancing Text-Driven Chest X-Ray Generation with Policy-Based Reinforcement Learning. CoRR abs/2403.06516 (2024) - [i18]Woojung Han, Seil Kang, Kyobin Choo, Seong Jae Hwang:
CoBra: Complementary Branch Fusing Class and Semantic Knowledge for Robust Weakly Supervised Semantic Segmentation. CoRR abs/2403.08801 (2024) - [i17]Seil Kang, Donghyun Kim, Junhyeok Kim, Hyo Kyung Lee, Seong Jae Hwang:
WoLF: Wide-scope Large Language Model Framework for CXR Understanding. CoRR abs/2403.15456 (2024) - [i16]Donghyun Kim, Seil Kang, Seong Jae Hwang:
FALCON: Frequency Adjoint Link with CONtinuous Density Mask for Fast Single Image Dehazing. CoRR abs/2407.00972 (2024) - [i15]Kyobin Choo, Youngjun Jun, Mijin Yun, Seong Jae Hwang:
Slice-Consistent 3D Volumetric Brain CT-to-MRI Translation with 2D Brownian Bridge Diffusion Model. CoRR abs/2407.05059 (2024) - [i14]Yumin Kim, Gayoon Choi, Seong Jae Hwang:
Parameter Efficient Fine Tuning for Multi-scanner PET to PET Reconstruction. CoRR abs/2407.07517 (2024) - [i13]Gayoon Choi, Taejin Jeong, Sujung Hong, Jaehoon Joo, Seong Jae Hwang:
DragText: Rethinking Text Embedding in Point-based Image Editing. CoRR abs/2407.17843 (2024) - 2023
- [j4]Mahbaneh Eshaghzadeh Torbati
, Davneet S. Minhas, Charles M. Laymon, Pauline Maillard
, James D. Wilson
, Chang-Le Chen, Ciprian M. Crainiceanu, Charles DeCarli
, Seong Jae Hwang
, Dana L. Tudorascu:
MISPEL: A supervised deep learning harmonization method for multi-scanner neuroimaging data. Medical Image Anal. 89: 102926 (2023) - [j3]Anthony Sicilia, Xingchen Zhao, Seong Jae Hwang
:
Domain adversarial neural networks for domain generalization: when it works and how to improve. Mach. Learn. 112(7): 2685-2721 (2023) - [c20]Kai Tzu-iunn Ong, Hana Kim, Minjin Kim, Jinseong Jang, Beomseok Sohn
, Yoon Seong Choi, Dosik Hwang, Seong Jae Hwang, Jinyoung Yeo:
Evidence-Empowered Transfer Learning for Alzheimer's Disease. ISBI 2023: 1-5 - [i12]Kai Tzu-iunn Ong
, Hana Kim, Minjin Kim, Jinseong Jang, Beomseok Sohn, Yoon Seong Choi, Dosik Hwang, Seong Jae Hwang, Jinyoung Yeo:
Evidence-empowered Transfer Learning for Alzheimer's Disease. CoRR abs/2303.01105 (2023) - 2022
- [c19]Katherine Atwell, Anthony Sicilia, Seong Jae Hwang, Malihe Alikhani:
The Change that Matters in Discourse Parsing: Estimating the Impact of Domain Shift on Parser Error. ACL (Findings) 2022: 824-845 - [c18]Xingchen Zhao, Chang Liu, Anthony Sicilia, Seong Jae Hwang, Yun Fu:
Test-time Fourier Style Calibration for Domain Generalization. IJCAI 2022: 1721-1727 - [c17]Anthony Sicilia, Katherine Atwell, Malihe Alikhani, Seong Jae Hwang:
PAC-Bayesian domain adaptation bounds for multiclass learners. UAI 2022: 1824-1834 - [i11]Katherine Atwell, Anthony Sicilia, Seong Jae Hwang, Malihe Alikhani:
The Change that Matters in Discourse Parsing: Estimating the Impact of Domain Shift on Parser Error. CoRR abs/2203.11317 (2022) - [i10]Xingchen Zhao, Chang Liu, Anthony Sicilia, Seong Jae Hwang, Yun Fu:
Test-time Fourier Style Calibration for Domain Generalization. CoRR abs/2205.06427 (2022) - [i9]Anthony Sicilia, Katherine Atwell, Malihe Alikhani, Seong Jae Hwang:
PAC-Bayesian Domain Adaptation Bounds for Multiclass Learners. CoRR abs/2207.05685 (2022) - 2021
- [j2]Mahbaneh Eshaghzadeh Torbati, Davneet S. Minhas, Ghasan Ahmad, Erin O'Connor, John Muschelli, Charles M. Laymon, Zixi Yang, Ann D. Cohen, Howard J. Aizenstein, William E. Klunk
, Bradley T. Christian, Seong Jae Hwang, Ciprian M. Crainiceanu, Dana L. Tudorascu:
A multi-scanner neuroimaging data harmonization using RAVEL and ComBat. NeuroImage 245: 118703 (2021) - [c16]Sihyeon Kim, Sanghyeok Lee, Dasol Hwang, Jaewon Lee, Seong Jae Hwang, Hyunwoo J. Kim:
Point Cloud Augmentation with Weighted Local Transformations. ICCV 2021: 528-537 - [c15]Mahbaneh Eshaghzadeh Torbati, Dana L. Tudorascu, Davneet S. Minhas, Pauline Maillard, Charles DeCarli, Seong Jae Hwang:
Multi-scanner Harmonization of Paired Neuroimaging Data via Structure Preserving Embedding Learning. ICCVW 2021: 3277-3286 - [c14]Xin Ma, Guorong Wu, Seong Jae Hwang
, Won Hwa Kim:
Learning Multi-resolution Graph Edge Embedding for Discovering Brain Network Dysfunction in Neurological Disorders. IPMI 2021: 253-266 - [c13]Anthony Sicilia, Xingchen Zhao, Davneet S. Minhas, Erin O'Connor, Howard J. Aizenstein, William E. Klunk
, Dana L. Tudorascu, Seong Jae Hwang
:
Multi-Domain Learning By Meta-Learning: Taking Optimal Steps In Multi-Domain Loss Landscapes By Inner-Loop Learning. ISBI 2021: 650-654 - [c12]Xingchen Zhao, Anthony Sicilia, Davneet S. Minhas, Erin O'Connor, Howard J. Aizenstein, William E. Klunk
, Dana L. Tudorascu, Seong Jae Hwang
:
Robust White Matter Hyperintensity Segmentation On Unseen Domain. ISBI 2021: 1047-1051 - [c11]Anthony Sicilia, Xingchen Zhao, Anastasia Sosnovskikh, Seong Jae Hwang:
PAC Bayesian Performance Guarantees for Deep (Stochastic) Networks in Medical Imaging. MICCAI (3) 2021: 560-570 - [i8]Anthony Sicilia, Xingchen Zhao, Seong Jae Hwang:
Domain Adversarial Neural Networks for Domain Generalization: When It Works and How to Improve. CoRR abs/2102.03924 (2021) - [i7]Xingchen Zhao, Anthony Sicilia, Davneet S. Minhas, Erin O'Connor, Howard Aizenstein, William E. Klunk, Dana Tudorascu, Seong Jae Hwang:
Robust White Matter Hyperintensity Segmentation on Unseen Domain. CoRR abs/2102.06650 (2021) - [i6]Anthony Sicilia, Xingchen Zhao, Davneet S. Minhas, Erin O'Connor, Howard Aizenstein, William E. Klunk, Dana Tudorascu, Seong Jae Hwang:
Multi-Domain Learning by Meta-Learning: Taking Optimal Steps in Multi-Domain Loss Landscapes by Inner-Loop Learning. CoRR abs/2102.13147 (2021) - [i5]Anthony Sicilia, Xingchen Zhao, Anastasia Sosnovskikh, Seong Jae Hwang:
PAC Bayesian Performance Guarantees for Deep (Stochastic) Networks in Medical Imaging. CoRR abs/2104.05600 (2021) - [i4]Sihyeon Kim, Sanghyeok Lee, Dasol Hwang, Jaewon Lee, Seong Jae Hwang, Hyunwoo J. Kim:
Point Cloud Augmentation with Weighted Local Transformations. CoRR abs/2110.05379 (2021) - 2020
- [c10]Brian Falkenstein
, Adriana Kovashka
, Seong Jae Hwang
, S. Chakra Chennubhotla
:
Classifying Nuclei Shape Heterogeneity in Breast Tumors with Skeletons. ECCV Workshops (1) 2020: 310-323 - [c9]Wei Hao, Nicholas M. Vogt, Zihang Meng, Seong Jae Hwang
, Rebecca L. Koscik, Sterling C. Johnson, Barbara B. Bendlin, Vikas Singh:
Learning Amyloid Pathology Progression from Longitudinal PIB-PET Images in Preclinical Alzheimer's Disease. ISBI 2020: 572-576 - [i3]Won Hwa Kim, Mona Jalal, Seong Jae Hwang, Sterling C. Johnson, Vikas Singh:
Online Graph Completion: Multivariate Signal Recovery in Computer Vision. CoRR abs/2008.05060 (2020)
2010 – 2019
- 2019
- [j1]Seong Jae Hwang
, Nagesh Adluru, Won Hwa Kim, Sterling C. Johnson, Barbara B. Bendlin
, Vikas Singh:
Associations Between Positron Emission Tomography Amyloid Pathology and Diffusion Tensor Imaging Brain Connectivity in Pre-Clinical Alzheimer's Disease. Brain Connect. 9(2): 162-173 (2019) - [c8]Seong Jae Hwang
, Zirui Tao, Vikas Singh, Won Hwa Kim:
Conditional Recurrent Flow: Conditional Generation of Longitudinal Samples With Applications to Neuroimaging. ICCV 2019: 10691-10700 - [c7]Seong Jae Hwang
, Joonseok Lee
, Balakrishnan Varadarajan, Ariel Gordon, Zheng Xu, Apostol Natsev:
Large-Scale Training Framework for Video Annotation. KDD 2019: 2394-2402 - [c6]Seong Jae Hwang, Ronak Mehta, Hyunwoo J. Kim, Sterling C. Johnson, Vikas Singh:
Sampling-free Uncertainty Estimation in Gated Recurrent Units with Applications to Normative Modeling in Neuroimaging. UAI 2019: 809-819 - 2018
- [c5]Seong Jae Hwang
, Sathya N. Ravi
, Zirui Tao, Hyunwoo J. Kim, Maxwell D. Collins, Vikas Singh:
Tensorize, Factorize and Regularize: Robust Visual Relationship Learning. CVPR 2018: 1014-1023 - [i2]Seong Jae Hwang, Ronak Mehta, Vikas Singh:
Sampling-free Uncertainty Estimation in Gated Recurrent Units with Exponential Families. CoRR abs/1804.07351 (2018) - [i1]Seong Jae Hwang, Zirui Tao, Won Hwa Kim, Vikas Singh:
Conditional Recurrent Flow: Conditional Generation of Longitudinal Samples with Applications to Neuroimaging. CoRR abs/1811.09897 (2018) - 2017
- [c4]Won Hwa Kim
, Mona Jalal
, Seong Jae Hwang
, Sterling C. Johnson, Vikas Singh:
Online Graph Completion: Multivariate Signal Recovery in Computer Vision. CVPR 2017: 5019-5027 - 2016
- [c3]Seong Jae Hwang
, Nagesh Adluru, Maxwell D. Collins, Sathya N. Ravi, Barbara B. Bendlin, Sterling C. Johnson, Vikas Singh:
Coupled Harmonic Bases for Longitudinal Characterization of Brain Networks. CVPR 2016: 2517-2525 - [c2]Won Hwa Kim
, Seong Jae Hwang
, Nagesh Adluru, Sterling C. Johnson, Vikas Singh:
Adaptive Signal Recovery on Graphs via Harmonic Analysis for Experimental Design in Neuroimaging. ECCV (6) 2016: 188-205 - 2015
- [c1]Seong Jae Hwang
, Maxwell D. Collins, Sathya N. Ravi
, Vamsi K. Ithapu, Nagesh Adluru, Sterling C. Johnson, Vikas Singh:
A Projection Free Method for Generalized Eigenvalue Problem with a Nonsmooth Regularizer. ICCV 2015: 1841-1849
Coauthor Index
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last updated on 2024-08-25 20:06 CEST by the dblp team
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