- A. W. Mulyadi, E. Jun and H.-I. Suk, “Uncertainty-Aware Variational-Recurrent Imputation Network for Clinical Time Series,” in IEEE Transactions on Cybernetics, 2021, doi: 10.1109/TCYB.2021.3053599.
- E. Jun, A. W. Mulyadi, J. Choi and H.-I. Suk, “Uncertainty-Gated Stochastic Sequential Model for EHR Mortality Prediction,” in IEEE Transactions on Neural Networks and Learning Systems, 2020, doi: 10.1109/TNNLS.2020.3016670.
W. Jung, A. W. Mulyadi, and H.-I. Suk, “Unified Modeling of Imputation, Forecasting, and Prediction for AD Progression,” 2019 Medical Image Computing and Computer Assisted Intervention (MICCAI), Shenzhen, China, 2019, doi: 10.1007/978-3-030-32251-9_19.
E. Jun*, A. W. Mulyadi*, and H.-I. Suk, “Stochastic Imputation and Uncertainty-Aware Attention to EHR for Mortality Prediction,” 2019 International Joint Conference on Neural Networks (IJCNN), Budapest, Hungary, 2019, pp. 1-7, doi: 10.1109/IJCNN.2019.8852132. *) Equally contributed.
- A. W. Mulyadi, C. Machbub, A. S. Prihatmanto, and B.-K. Sin, “Design of Music Learning Assistant Based on Audio Music and Music Score Recognition,” 한국멀티미디어학회논문지, vol. 19, no. 5, pp. 826–836, May 2016.
- A. W. Mulyadi, B.-K. Sin, “Music Learning Assistant Using Audio-Visual Analysis,” 한국정보과학회 2015년 동계학술발표회 논문집, pp. 733 - 734, 2015.