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Bonggun Shin
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2020 – today
- 2023
- [c12]Yeachan Kim, Seongyeon Kim, Ihyeok Seo, Bonggun Shin:
Phase-shifted adversarial training. UAI 2023: 1068-1077 - [i14]Yeachan Kim, Seongyeon Kim, Ihyeok Seo, Bonggun Shin:
Phase-shifted Adversarial Training. CoRR abs/2301.04785 (2023) - [i13]Daeseok Lee, Bonggun Shin, Jeunghyun Byun:
Boosting Convolutional Neural Networks' Protein Binding Site Prediction Capacity Using SE(3)-invariant transformers, Transfer Learning and Homology-based Augmentation. CoRR abs/2303.08818 (2023) - [i12]Yeachan Kim, Bonggun Shin:
Learning From Drift: Federated Learning on Non-IID Data via Drift Regularization. CoRR abs/2309.07189 (2023) - 2022
- [c11]Dongpin Oh, Bonggun Shin:
Improving Evidential Deep Learning via Multi-Task Learning. AAAI 2022: 7895-7903 - [c10]Yeachan Kim, Bonggun Shin:
In Defense of Core-set: A Density-aware Core-set Selection for Active Learning. KDD 2022: 804-812 - [i11]Yeachan Kim, Bonggun Shin:
In Defense of Core-set: A Density-aware Core-set Selection for Active Learning. CoRR abs/2206.04838 (2022) - [i10]Dongpin Oh, Dae Lee, Jeunghyun Byun, Bonggun Shin:
Improving group robustness under noisy labels using predictive uncertainty. CoRR abs/2212.07026 (2022) - 2021
- [c9]Jing Zhang, Bonggun Shin, Jinho D. Choi, Joyce C. Ho:
SMAT: An Attention-Based Deep Learning Solution to the Automation of Schema Matching. ADBIS 2021: 260-274 - [c8]Bonggun Shin, Sungsoo Park, JinYeong Bak
, Joyce C. Ho:
Controlled molecule generator for optimizing multiple chemical properties. CHIL 2021: 146-153 - [c7]Yeachan Kim, Bonggun Shin:
An Interpretable Framework for Drug-Target Interaction with Gated Cross Attention. MLHC 2021: 337-353 - [i9]Yeachan Kim, Bonggun Shin:
An Interpretable Framework for Drug-Target Interaction with Gated Cross Attention. CoRR abs/2109.08360 (2021) - [i8]Dongpin Oh, Bonggun Shin:
Improving evidential deep learning via multi-task learning. CoRR abs/2112.09368 (2021) - 2020
- [i7]Bonggun Shin, Sungsoo Park, JinYeong Bak, Joyce C. Ho:
Controlled Molecule Generator for Optimizing Multiple Chemical Properties. CoRR abs/2010.13908 (2020)
2010 – 2019
- 2019
- [c6]Bonggun Shin, Julien Hogan, Andrew B. Adams, Raymond J. Lynch, Rachel E. Patzer, Jinho D. Choi:
Multimodal Ensemble Approach to Incorporate Various Types of Clinical Notes for Predicting Readmission. BHI 2019: 1-4 - [c5]Bonggun Shin, Hao Yang, Jinho D. Choi:
The Pupil Has Become the Master: Teacher-Student Model-Based Word Embedding Distillation with Ensemble Learning. IJCAI 2019: 3439-3445 - [c4]Bonggun Shin, Sungsoo Park, Keunsoo Kang, Joyce C. Ho:
Self-Attention Based Molecule Representation for Predicting Drug-Target Interaction. MLHC 2019: 230-248 - [i6]Bonggun Shin, Hao Yang, Jinho D. Choi:
The Pupil Has Become the Master: Teacher-Student Model-Based Word Embedding Distillation with Ensemble Learning. CoRR abs/1906.00095 (2019) - [i5]Bonggun Shin, Julien Hogan, Andrew B. Adams, Raymond J. Lynch, Rachel E. Patzer, Jinho D. Choi:
Multimodal Ensemble Approach to Incorporate Various Types of Clinical Notes for Predicting Readmission. CoRR abs/1906.01498 (2019) - [i4]Bonggun Shin, Sungsoo Park, Keunsoo Kang, Joyce C. Ho:
Self-Attention Based Molecule Representation for Predicting Drug-Target Interaction. CoRR abs/1908.06760 (2019) - 2017
- [c3]Bonggun Shin, Falgun H. Chokshi, Timothy Lee, Jinho D. Choi:
Classification of radiology reports using neural attention models. IJCNN 2017: 4363-4370 - [c2]Bonggun Shin, Timothy Lee, Jinho D. Choi:
Lexicon Integrated CNN Models with Attention for Sentiment Analysis. WASSA@EMNLP 2017: 149-158 - [i3]Bonggun Shin, Falgun H. Chokshi, Timothy Lee, Jinho D. Choi:
Classification of Radiology Reports Using Neural Attention Models. CoRR abs/1708.06828 (2017) - 2016
- [i2]Bonggun Shin, Timothy Lee, Jinho D. Choi:
Lexicon Integrated CNN Models with Attention for Sentiment Analysis. CoRR abs/1610.06272 (2016) - 2012
- [i1]Bonggun Shin, Alice Oh:
Bayesian Group Nonnegative Matrix Factorization for EEG Analysis. CoRR abs/1212.4347 (2012) - 2011
- [c1]Bonggun Shin, Sungho Jo:
Pattern-preserving-based motion imitation for robots. URAI 2011: 20-25
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