Byung-Hak Kim

Publication Activity (10 Years)

Years Active: 2010-2023
Publications (10 Years): 15

Top Topics

Domain Adaptation

Medical Diagnosis

Weakly Supervised

Top Venues

Publications

Makiya Nakashima, Donna Salem, HW Wilson Tang, Christopher Nguyen, Tae-Hyun Hwang, Ding Zhao, Byung-Hak Kim, Deborah Kwon, David Chen
Reducing Contextual Bias in Cardiac Magnetic Resonance Imaging Deep Learning Using Contrastive Self-Supervision. MLHC (2023)
Jielin Qiu, Peide Huang, Makiya Nakashima, Jaehyun Lee, Jiacheng Zhu, W. H. Wilson Tang, Pohao Chen, Christopher Nguyen, Byung-Hak Kim, Debbie Kwon, Douglas Weber, Ding Zhao, David Chen
Multimodal Representation Learning of Cardiovascular Magnetic Resonance Imaging. CoRR (2023)
Weiyao Wang, Byung-Hak Kim, Varun Ganapathi
RegCLR: A Self-Supervised Framework for Tabular Representation Learning in the Wild. CoRR (2022)
Byung-Hak Kim, Zhongfen Deng, Philip S. Yu, Varun Ganapathi
Can Current Explainability Help Provide References in Clinical Notes to Support Humans Annotate Medical Codes? CoRR (2022)
Byung-Hak Kim, Zhongfen Deng, Philip S. Yu, Varun Ganapathi
Can Current Explainability Help Provide References in Clinical Notes to Support Humans Annotate Medical Codes? LOUHI@EMNLP (2022)
Byung-Hak Kim
Medical Codes Prediction from Clinical Notes: From Human Coders to Machines. CoRR (2022)
Byung-Hak Kim, Varun Ganapathi
Read, Attend, and Code: Pushing the Limits of Medical Codes Prediction from Clinical Notes by Machines. CoRR (2021)
Byung-Hak Kim, Varun Ganapathi
Read, Attend, and Code: Pushing the Limits of Medical Codes Prediction from Clinical Notes by Machines. MLHC (2021)
Byung-Hak Kim, Seshadri Sridharan, Andy Atwal, Varun Ganapathi
Deep Claim: Payer Response Prediction from Claims Data with Deep Learning. CoRR (2020)
Byung-Hak Kim, Varun Ganapathi
LumièreNet: Lecture Video Synthesis from Audio. CoRR (2019)
Byung-Hak Kim
Deep Learning to Predict Student Outcomes. CoRR (2019)
Byung-Hak Kim, Ethan Vizitei, Varun Ganapathi
GritNet: Student Performance Prediction with Deep Learning. EDM (2018)
Byung-Hak Kim, Ethan Vizitei, Varun Ganapathi
GritNet: Student Performance Prediction with Deep Learning. CoRR (2018)
Byung-Hak Kim, Ethan Vizitei, Varun Ganapathi
GritNet 2: Real-Time Student Performance Prediction with Domain Adaptation. CoRR (2018)
Kyu J. Han, Seongjun Hahm, Byung-Hak Kim, Jungsuk Kim, Ian R. Lane
Deep Learning-Based Telephony Speech Recognition in the Wild. INTERSPEECH (2017)
Byung-Hak Kim, Henry D. Pfister
An Iterative Joint Linear-Programming Decoding of LDPC Codes and Finite-State Channels. ICC (2011)
Byung-Hak Kim, Henry D. Pfister
Joint Decoding of LDPC Codes and Finite-State Channels via Linear-Programming CoRR (2011)
Byung-Hak Kim, Henry D. Pfister
Joint Decoding of LDPC Codes and Finite-State Channels Via Linear-Programming. IEEE J. Sel. Top. Signal Process. 5 (8) (2011)
Byung-Hak Kim, Henry D. Pfister
On the Joint Decoding of LDPC Codes and Finite-State Channels via Linear Programming CoRR (2010)
Byung-Hak Kim, Arvind Yedla, Henry D. Pfister
Message-Passing Inference on a Factor Graph for Collaborative Filtering CoRR (2010)
Byung-Hak Kim, Henry D. Pfister
On the joint decoding of LDPC codes and finite-state channels via linear programming. ISIT (2010)
Byung-Hak Kim, Arvind Yedla, Henry D. Pfister
IMP: A Message-Passing Algorithmfor Matrix Completion CoRR (2010)
Byung-Hak Kim, Henry D. Pfister
An Iterative Joint Linear-Programming Decoding of LDPC Codes and Finite-State Channels CoRR (2010)