Seokho Kang
Cited by
Cited by
Conditional molecular design with deep generative models
S Kang, K Cho
Journal of Chemical Information and Modeling 59 (1), 43-52, 2019
Approximating support vector machine with artificial neural network for fast prediction
S Kang, S Cho
Expert Systems with Applications 41 (10), 4989-4995, 2014
Constructing a multi-class classifier using one-against-one approach with different binary classifiers
S Kang, S Cho, P Kang
Neurocomputing 149, 677-682, 2015
Molecular geometry prediction using a deep generative graph neural network
E Mansimov, O Mahmood, S Kang, K Cho
Scientific Reports 9, 20381, 2019
An efficient and effective ensemble of support vector machines for anti-diabetic drug failure prediction
S Kang, P Kang, T Ko, S Cho, S Rhee, KS Yu
Expert Systems with Applications 42 (9), 4265-4273, 2015
Multi-class classification via heterogeneous ensemble of one-class classifiers
S Kang, S Cho, P Kang
Engineering Applications of Artificial Intelligence 43, 35-43, 2015
Deep-learning-based inverse design model for intelligent discovery of organic molecules
K Kim, S Kang, J Yoo, Y Kwon, Y Nam, D Lee, I Kim, YS Choi, Y Jung, ...
npj Computational Materials 4, 67, 2018
Mining the relationship between production and customer service data for failure analysis of industrial products
S Kang, E Kim, J Shim, S Cho, W Chang, J Kim
Computers & Industrial Engineering 106, 137-146, 2017
An intelligent virtual metrology system with adaptive update for semiconductor manufacturing
S Kang, P Kang
Journal of Process Control 52, 66-74, 2017
Using wafer map features to better predict die-level failures in final test
S Kang, S Cho, D An, J Rim
IEEE Transactions on Semiconductor Manufacturing 28 (3), 431-437, 2015
Efficient feature selection based on random forward search for virtual metrology modeling
S Kang, D Kim, S Cho
IEEE Transactions on Semiconductor Manufacturing 29 (4), 391-398, 2016
On effectiveness of transfer learning approach for neural network-based virtual metrology modeling
S Kang
IEEE Transactions on Semiconductor Manufacturing 31 (1), 149-155, 2018
Active learning of convolutional neural network for cost-effective wafer map pattern classification
J Shim, S Kang, S Cho
IEEE Transactions on Semiconductor Manufacturing 33 (2), 258-266, 2020
Personalized prediction of drug efficacy for diabetes treatment via patient-level sequential modeling with neural networks
S Kang
Artificial Intelligence in Medicine 85, 1-6, 2018
Joint modeling of classification and regression for improving faulty wafer detection in semiconductor manufacturing
S Kang
Journal of Intelligent Manufacturing 31 (2), 319-326, 2020
Product failure prediction with missing data
S Kang, E Kim, J Shim, W Chang, S Cho
International Journal of Production Research 56 (14), 4849-4859, 2018
Neural message passing for NMR chemical shift prediction
Y Kwon, D Lee, YS Choi, M Kang, S Kang
Journal of Chemical Information and Modeling 60 (4), 2024-2030, 2020
Energy-saving decision making framework for HVAC with usage logs
J Park, S Cho, S Lee, S Kang, YS Kim, JY Kim, DS Choi
Energy and Buildings 108, 346-357, 2015
Optimal construction of one-against-one classifier based on meta-learning
S Kang, S Cho
Neurocomputing 167, 459-466, 2015
Locally linear ensemble for regression
S Kang, P Kang
Information Sciences 432, 199-209, 2018
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