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2020 – today
- 2024
[j14]Naae Kwon, Yuenkyung Yoo
, Byunghan Lee:
Novel Curriculum Learning Strategy Using Class-Based TF-IDF for Enhancing Personality Detection in Text. IEEE Access 12: 87873-87882 (2024)- [j13]Naae Kwon, Yuenkyung Yoo, Byunghan Lee:
Class conditioned text generation with style attention mechanism for embracing diversity. Appl. Soft Comput. 163: 111893 (2024) - [j12]HyunGi Kim, Siwon Kim, Seonwoo Min, Byunghan Lee:
Contrastive Time-Series Anomaly Detection. IEEE Trans. Knowl. Data Eng. 36(10): 5053-5065 (2024) - 2023
- [j11]Minseo Kang, Byunghan Lee:
TiCTok: Time-Series Anomaly Detection With Contrastive Tokenization. IEEE Access 11: 81011-81020 (2023) - [c8]Subin Kim, Yunseon Choi, Byunghan Lee:
Considerations in Evaluation of Deep Hashing Networks for Information Retrieval System. ISOCC 2023: 149-150 - 2022
- [j10]Seonwoo Min, Byunghan Lee, Sungroh Yoon:
TargetNet: functional microRNA target prediction with deep neural networks. Bioinform. 38(3): 671-677 (2022) - [c7]Siwon Kim, Kukjin Choi, Hyun-Soo Choi, Byunghan Lee, Sungroh Yoon:
Towards a Rigorous Evaluation of Time-Series Anomaly Detection. AAAI 2022: 7194-7201 - 2021
- [j9]Seonwoo Min, Seunghyun Park, Siwon Kim, Hyun-Soo Choi, Byunghan Lee, Sungroh Yoon:
Pre-Training of Deep Bidirectional Protein Sequence Representations With Structural Information. IEEE Access 9: 123912-123926 (2021) - [j8]Sunyoung Kwon, Gyuwan Kim, Byunghan Lee, Jongsik Chun, Sungroh Yoon, Young-Han Kim:
NASCUP: Nucleic Acid Sequence Classification by Universal Probability. IEEE Access 9: 162779-162791 (2021) - [j7]Byunghan Lee, Hyeyoung Min, Sungroh Yoon:
MUGAN: multi-GPU accelerated AmpliconNoise server for rapid microbial diversity assessment. Bioinform. 37(11): 1562-1570 (2021) - [i12]Jeonghee Jo, Bumju Kwak, Byunghan Lee, Sungroh Yoon:
Flexible dual-branched message passing neural network for quantum mechanical property prediction with molecular conformation. CoRR abs/2106.07273 (2021) - [i11]Bumju Kwak, Jeonghee Jo, Byunghan Lee, Sungroh Yoon:
Geometry-aware Transformer for molecular property prediction. CoRR abs/2106.15516 (2021) - [i10]Seonwoo Min, Byunghan Lee, Sungroh Yoon:
TargetNet: Functional microRNA Target Prediction with Deep Neural Networks. CoRR abs/2107.11381 (2021) - [i9]Siwon Kim, Kukjin Choi, Hyun-Soo Choi, Byunghan Lee, Sungroh Yoon:
Towards a Rigorous Evaluation of Time-series Anomaly Detection. CoRR abs/2109.05257 (2021) - 2020
- [j6]Byunghan Lee:
Deep Learning-Based microRNA Target Prediction Using Experimental Negative Data. IEEE Access 8: 197908-197916 (2020) - [c6]Seonwoo Min, Hyun-Soo Choi, Hyeongrok Han, Minji Seo, Jin-Kook Kim, Junsang Park, Sunghoon Jung, Il-Young Oh, Byunghan Lee, Sungroh Yoon:
Bag of Tricks for Electrocardiogram Classification With Deep Neural Networks. CinC 2020: 1-4
2010 – 2019
- 2019
- [c5]Ho Bae, Byunghan Lee, Sunyoung Kwon, Sungroh Yoon:
DNA Steganalysis Using Deep Recurrent Neural Networks. PSB 2019: 88-99 - 2018
- [j5]Junghwan Baek, Byunghan Lee, Sunyoung Kwon, Sungroh Yoon:
LncRNAnet: long non-coding RNA identification using deep learning. Bioinform. 34(22): 3889-3897 (2018) - [j4]Seunghyun Park, Hyun-Soo Choi, Byunghan Lee, Jongsik Chun, Joong-Ho Won, Sungroh Yoon:
hc-OTU: A Fast and Accurate Method for Clustering Operational Taxonomic Units Based on Homopolymer Compaction. IEEE ACM Trans. Comput. Biol. Bioinform. 15(2): 441-451 (2018) - [i8]Jaekoo Lee, Byunghan Lee, Jongyoon Song, Jaesik Yoon, Yongsik Lee, Donghun Lee, Sungroh Yoon:
Deep Learning on Key Performance Indicators for Predictive Maintenance in SAP HANA. CoRR abs/1804.05497 (2018) - 2017
- [j3]Seonwoo Min, Byunghan Lee, Sungroh Yoon:
Deep learning in bioinformatics. Briefings Bioinform. 18(5): 851-869 (2017) - [i7]Ho Bae, Byunghan Lee, Sunyoung Kwon, Sungroh Yoon:
DNA Steganalysis Using Deep Recurrent Neural Networks. CoRR abs/1704.08443 (2017) - 2016
- [j2]Hyun-Soo Choi, Byunghan Lee, Sungroh Yoon:
Biometric Authentication Using Noisy Electrocardiograms Acquired by Mobile Sensors. IEEE Access 4: 1266-1273 (2016) - [c4]Byunghan Lee, Junghwan Baek, Seunghyun Park, Sungroh Yoon:
deepTarget: End-to-end Learning Framework for microRNA Target Prediction using Deep Recurrent Neural Networks. BCB 2016: 434-442 - [c3]Taesup Moon, Seonwoo Min, Byunghan Lee, Sungroh Yoon:
Neural Universal Discrete Denoiser. NIPS 2016: 4772-4780 - [i6]Seonwoo Min, Byunghan Lee, Sungroh Yoon:
Deep Learning in Bioinformatics. CoRR abs/1603.06430 (2016) - [i5]Byunghan Lee, Junghwan Baek, Seunghyun Park, Sungroh Yoon:
deepTarget: End-to-end Learning Framework for microRNA Target Prediction using Deep Recurrent Neural Networks. CoRR abs/1603.09123 (2016) - 2015
- [i4]Sungmin Lee, Byunghan Lee, Sei Joon Kim, Sunyoung Kwon, Sungroh Yoon:
Will solid-state drives accelerate your bioinformatics? In-depth profiling, performance analysis, and beyond. CoRR abs/1502.02223 (2015) - [i3]Byunghan Lee, Taesup Moon, Sungroh Yoon, Tsachy Weissman:
DUDE-Seq: Fast Universal Denoising of Nucleotide Sequences. CoRR abs/1511.04836 (2015) - [i2]Sunyoung Kwon, Gyuwan Kim, Byunghan Lee, Sungroh Yoon, Young-Han Kim:
NASCUP: Nucleic Acid Sequence Classification by Universal Probability. CoRR abs/1511.04944 (2015) - [i1]Byunghan Lee, Taehoon Lee, Byunggook Na, Sungroh Yoon:
DNA-Level Splice Junction Prediction using Deep Recurrent Neural Networks. CoRR abs/1512.05135 (2015) - 2014
- [j1]Sunyoung Kwon, Byunghan Lee, Sungroh Yoon:
CASPER: context-aware scheme for paired-end reads from high-throughput amplicon sequencing. BMC Bioinform. 15(S-9): S10 (2014) - 2013
- [c2]Sunyoung Kwon, Seunghyun Park, Byunghan Lee, Sungroh Yoon:
In-depth analysis of interrelation between quality scores and real errors in illumina reads. EMBC 2013: 635-638 - 2012
- [c1]Byunghan Lee, Joonhong Park, Sungroh Yoon:
Rapid and Robust Denoising of Pyrosequenced Amplicons for Metagenomics. ICDM 2012: 954-959
Coauthor Index
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