Publications
Papers( IJ International Journal, DJ Domestic Journal, IC International Conference, DC Domestic Conference, PR Preprint)
2023 (5 - IJ: 2, IC: 2, DJ:0, DC:1, PR:0)
[IJ-02] Jeongwhan Choi and Noseong Park, "Graph Neural Rough Differential Equations for Traffic Forecasting", ACM Transactions on Intelligent Systems and Technology (TIST) 2023. [IF=10.489][Paper]
[IC-07] Jeongwhan Choi, Seoyoung Hong, Noseong Park and Sung-Bae Cho , "GREAD: Graph Reaction-Diffusion Networks," In International Conference on Machine Learning (ICML), 2023. [Acceptance Rate 27.94% (1,827/6,538)] [arXiv][Paper]
[IC-06] Jeongwhan Choi, Seoyoung Hong, Noseong Park and Sung-Bae Cho , "Blurring-Sharpening Process Models for Collaborative Filtering," In Proceedings of the ACM Conference on Research and Development in Information Retrieval (SIGIR), 2023. [Paper Acceptance rate: 20.1% (165/822)][arXiv][GitHub]
[DC-07] Jeongwhan Choi and Duksan Ryu, "Graph Convolution-based Collaborative Filtering for Web Service QoS Ranking", In Proceedings of the 25th Korea Conference on Software Engineering (KCSE 2023), Feb. 2023. pp. 58-67.
[IJ-01] Hwangyong Choi, Jeongwhan Choi, Jeehyun Hwang, Kookjin Lee, Dongeun Lee and Noseong Park, "Climate Modeling with Neural Advection-Diffusion Equation," Knowledge and Information Systems, Jan. 2023. [IF=3.205 (2021) Five year impact factor][pdf]
2022 (4 - IJ: 0, IC: 3, DJ:0, DC:0, PR:1)
[PR-01] Jaehoon Lee, Chan Kim, Gyumin Lee, Haksoo Lim, Jeongwhan Choi, Kookjin Lee, Dongeun Lee, Sanghyun Hong and Noseong Park, "Time Series Forecasting with Hypernetworks Generating Parameters in Advance," arXiv preprint arXiv: Arxiv-2211.12034, 2022. [arXiv]
[IC-05] Seoyoung Hong, Heejoo Shin, Jeongwhan Choi, and Noseong Park, "Prediction-based One-shot Dynamic Parking Pricing," In Proceedings of the 31st ACM International Conference on Information and Knowledge Management (CIKM), 2022. [Paper][arXiv][GitHub][Regular Paper Acceptance rate: 23.23% ]
[IC-04] Jeongwhan Choi, Hwangyong Choi, Jeehyun Hwang and Noseong Park, "Graph Neural Controlled Differential Equations for Traffic Forecasting," In AAAI, 2022. [arXiv][Paper][GitHub][Oral Paper Selected (Acceptance rate: 5.5%)][Regular Paper Acceptance rate: 14.2% (1,161/8,198)] [Overall Acceptance rate: 15.2% (1,370/9,020)]
[IC-03] Taeyong Kong, Taeri Kim, Jinsung Jeon, Jeongwhan Choi, Yeon-Chang Lee, Noseong Park and Sang-Wook Kim, "Linear, or Non-Linear, That is the Question!," In Proceedings of the 15th ACM International Web Search and Data Mining Conference (WSDM), 2022. [arXiv][GitHub][Regular Paper Acceptance rate: 15.8% (80/505)] [Overall Acceptance Rate: 18% (315/1,765) ]
2021 (6 - IJ: 0, IC: 2, DJ: 2, DC: 2, PR: 0)
[DC-06] Jeongwhan Choi and Duksan Ryu, "Self-Supervised Learning Using Feature Subsets of Software Defect Data", In Proceedings of the Korea Software Congress (KSC), Dec. 2021, pp.203-205.
[IC-02] Jeehyun Hwang, Jeongwhan Choi, Hwangyong Choi, Kookjin Lee, Dongeun Lee and Noseong Park, "Climate Modeling with Neural Diffusion Equations", In Proceedings of the 21st IEEE International Conference on Data Mining (ICDM), 2021. [pdf from arxiv.org] [GitHub] [Regular paper acceptance rate: 9.9% (98/990)] [Overall Acceptance Rate: 20% (198/990)]
[DJ-04] Jeongwhan Choi and Duksan Ryu, "Bayesian Optimization Framework for Improved Cross-Version Defect Prediction", KIPS Transactions on Software and Data Engineering (KTSDE), Vol. 10, No. 9, pp. 339-348, Sep. 2021.
[IC-01] Jeongwhan Choi, Jinsung Jeon, and Noseong Park, "LT-OCF: Learnable-Time ODE-based Collaborative Filtering", In Proceedings of the 30th ACM International Conference on Information and Knowledge Management (CIKM), 2021. [pdf from arxiv.org] [Github] [Regular paper acceptance rate: 21.7% (271/1,251)] [Overall Acceptance rate: 22% (1,101/4,989)]
[DC-05] Jeongwhan Choi and Duksan Ryu, "Bayesian Optimization Framework for Cross-Version Defect Prediction", In Proceedings of the 23rd Korea Conference on Software Engineering (KCSE 2021), 2021, pp. 63-72. [Best Paper][pdf][recorded video]
[DJ-03] Jeongwhan Choi, Jiwon Choi, Duksan Ryu and Suntae Kim, "Improved Prediction for Configuration Bug Report Using Text Mining and Dimensionality Reduction," Journal of KIISE, 2021, Vol. 48, No. 1, pp. 35-42.
2020 (3 - IJ: 0, IC: 0, DJ: 0, DC: 3, PR: 0)
[DC-04] Jeongwhan Choi and Duksan Ryu, "A Study on the Applicability of Transfer Learning Techniques for Cross-Project Defect Regression," In Proceedings of the Korea Software Congress (KSC), 2020, pp. 150 - 152.
[DC-03] Jeongwhan Choi, Duksan Ryu, and Suntae Kim, “Comparative Study of Transfer Learning Models for Cross-Project Automotive Software Defect Prediction,” In Proceedings of the Korea Computer Congress (KCC), 2020, pp. 257–259.
[DC-02] Jeongwhan Choi, Jiwon Choi, Duksan Ryu, and Suntae Kim, “Prediction for Configuration Bug Report Using Text Mining,” In Proceedings of the 22nd Korea Conference on Software Engineering (KCSE 2020), 2020, pp. 350–357. [pdf]
2019 (2 - IJ: 0, IC: 0, DJ: 1, DC: 1, PR: 0)
[DJ-02] Jeongwhan Choi, Jiwoo Noh, and Suntae Kim, “Prediction Techniques for Difficulty Level of Hanja Using Multiple Linear Regression,” J. Inst. Internet, Broadcast. Commun., vol. 19, no. 6, 2019.
[DC-01] Seounghan Song, Jeongwhan Choi, Mingu Kang, and Cheoljung Yoo, “A Software Module That Analyzes the Relationship Between Headline and Content of the Web Article: CHIMERA,” in The Proceedings of the 2019 KIIT DCS Summer Conference, vol. 14, pp. 437–440, 2019.
2018 (1 - IJ: 0, IC: 0, DJ: 1, DC: 0)
[DJ-01] Jeongwhan Choi, “Iceberg-Ship Classification in SAR Images Using Convolutional Neural Network with Transfer Learning,” J. Internet Comput. Serv., vol. 19, no. 4, pp. 35–44, 2018.