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Sungroh Yoon
Sungroh Yoon
Professor, Electrical and Computer Engineering & Artificial Intelligence, Seoul National University
Verified email at snu.ac.kr - Homepage
Title
Cited by
Cited by
Year
Deep Learning in Bioinformatics
S Min, B Lee, S Yoon
Briefings in Bioinformatics 18 (5), 851-869, 2016
17212016
FickleNet: Weakly and Semi-Supervised Semantic Image Segmentation Using Stochastic Inference
J Lee, E Kim, S Lee, J Lee, S Yoon
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 5267-5276, 2019
4802019
ILVR: Conditioning Method for Denoising Diffusion Probabilistic Models
J Choi, S Kim, Y Jeong, Y Gwon, S Yoon
ICCV 2021 Oral (arXiv preprint arXiv:2108.02938), 2021
428*2021
Glow-TTS: A Generative Flow for Text-to-Speech via Monotonic Alignment Search
J Kim, S Kim, J Kong, S Yoon
NeurIPS 2020 Oral (arXiv preprint arXiv:2005.11129), 2020
3922020
Patch SVDD: Patch-level SVDD for anomaly detection and segmentation
J Yi, S Yoon
Proceedings of the Asian Conference on Computer Vision, 2020
3782020
How generative adversarial networks and their variants work: An overview
Y Hong, U Hwang, J Yoo, S Yoon
ACM Computing Surveys (CSUR) 52 (1), 1-43, 2019
3612019
RNA design rules from a massive open laboratory
J Lee, W Kladwang, M Lee, D Cantu, M Azizyan, H Kim, A Limpaecher, ...
Proceedings of the National Academy of Sciences 111 (6), 2122-2127, 2014
3422014
Spiking-YOLO: Spiking Neural Network for Real-time Object Detection
S Kim, S Park, B Na, S Yoon
AAAI 2020 (arXiv preprint arXiv:1903.06530), 2020
312*2020
Deep learning improves prediction of CRISPR–Cpf1 guide RNA activity
HK Kim, S Min, M Song, S Jung, JW Choi, Y Kim, S Lee, S Yoon, H Kim
Nature Biotechnology 36 (3), 239-241, 2018
2912018
Deep learning for anomaly detection in time-series data: Review, analysis, and guidelines
K Choi, J Yi, C Park, S Yoon
IEEE access 9, 120043-120065, 2021
2522021
Got target?: computational methods for microRNA target prediction and their extension
H Min, S Yoon
Experimental & molecular medicine 42 (4), 233-244, 2010
2472010
Anti-Adversarially Manipulated Attributions for Weakly and Semi-Supervised Semantic Segmentation
J Lee, E Kim, S Yoon
CVPR 2021 (arXiv preprint arXiv:2103.08896), 2021
1992021
Prediction of regulatory modules comprising microRNAs and target genes
S Yoon, G De Micheli
Bioinformatics 21 (suppl_2), ii93-ii100, 2005
1932005
FloWaveNet : A Generative Flow for Raw Audio
S Kim, S Lee, J Song, S Yoon
ICML 2019 (arXiv preprint arXiv:1811.02155), 2018
1922018
Predicting the efficiency of prime editing guide RNAs in human cells
HK Kim, G Yu, J Park, S Min, S Lee, S Yoon, HH Kim
Nature Biotechnology 39 (2), 198-206, 2021
1802021
SpCas9 activity prediction by DeepSpCas9, a deep learning–based model with high generalization performance
HK Kim, Y Kim, S Lee, S Min, JY Bae, JW Choi, J Park, D Jung, S Yoon, ...
Science advances 5 (11), eaax9249, 2019
1742019
Comprehensive ensemble in QSAR prediction for drug discovery
S Kwon, H Bae, J Jo, S Yoon
BMC bioinformatics 20, 1-12, 2019
1642019
Big/little deep neural network for ultra low power inference
E Park, D Kim, S Kim, YD Kim, G Kim, S Yoon, S Yoo
2015 international conference on hardware/software codesign and system …, 2015
1582015
Prediction of the sequence-specific cleavage activity of Cas9 variants
N Kim, HK Kim, S Lee, JH Seo, JW Choi, J Park, S Min, S Yoon, SR Cho, ...
Nature Biotechnology 38 (11), 1328-1336, 2020
1542020
BBAM: Bounding Box Attribution Map for Weakly Supervised Semantic and Instance Segmentation
J Lee, J Yi, C Shin, S Yoon
CVPR 2021 (arXiv preprint arXiv:2103.08907), 2021
1492021
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