Publications
Publications ( IJ International Journal, DJ Domestic Journal, IC International Conference, DC Domestic Conference, PR Preprint, W Workshop)
Preprint (4)
[PR-04] Jeongeun Lee, Seongku Kang, Won-Yong Shin, Jeongwhan Choi, Noseong Park, Dongha Lee, "Graph Signal Processing for Cross-Domain Recommendation", arXiv preprint arXiv: Arxiv-2407.12374. [arXiv]
[PR-03] Jeongwhan Choi*, Hyowon Wi*, Chaejeong Lee, Sung-Bae Cho, Dongha Lee, and Noseong Park, "RDGCL: Reaction-Diffusion Graph Contrastive Learning for Recommendation," arXiv preprint arXiv: Arxiv-2312.16563, 2023. [arXiv]
[PR-02] Yeon Uk Jeong, Jeongwhan Choi, Noseong Park, Jae Yong Ryu, and Yi Rang Kim, "Predicting Drug-Drug Interactions: A Deep Learning Approach with GCN-Based Collaborative Filtering," Available at SSRN 4640046, [link]
[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]
2025 (3 - IJ: 0, IC:2, DJ:0, DC:0, W:1)
[W-03] Seonkyu Lim, Jeongwhan Choi, Jaehoon Lee, Noseong Park, "FrAug: Enhanced Fraud Detection in Interbank Transfers via Augmented Account Features", In AI4TS Workshop at AAAI 2025.
[IC-17] Seonkyu Lim, Jeongwhan Choi, Jaehoon Lee, Noseong Park, "FrAug: Enhanced Fraud Detection in Interbank Transfers via Augmented Account Features", In IEEE BigComp, 2025.
[IC-16] Chaejeong Lee*, Jeongwhan Choi*, Hyowon Wi, Sung-Bae Cho, and Noseong Park, "SCONE: A Novel Stochastic Sampling to Generate Contrastive Views and Hard Negative Samples for Recommendation", In The 18th ACM International Conference on Web Search and Data Mining, 2025. [Acceptance rate: 17.3% (106/615)][arXiv]
2024 (9 - IJ: 1, IC:7, DJ:0, DC:0, W:1)
[W-02] Seonkyu Lim, Jeongwhan Choi, Jaehoon Lee, Noseong Park, "Enhanced Fraud Detection in Bank Transfers via Augmented Account Features", ACM ICAIF Workshop on Foundation Models for Time Series: Exploring New Frontiers (FM4TS), 2024. [Accepted for oral presentation][etnews][ZDNET KOREA]
[IJ-03] Taeyang Lee, Jeongwhan Choi, Inyeob Na, Insun Yoo, Sungil Woo, Kwang Jong Kim, Mikyung Park, Joonghwan Yang, Jeongguk Min, Seokwoo Lee, Noseong Park, Joonyoung Yang, "Graph-Based Representation Approach for Deep Learning of Organic Light-Emitting Diode Devices", Advanced Intelligent System. [IF=6.8][Paper]
[IC-15] Jeongwhan Choi*, Hyowon Wi*, Jayoung Kim, Yehjin Shin, Kookjin Lee, Nathaniel Trask, and Noseong Park, "Graph Convolutions Enrich the Self-Attention in Transformers!", In Conference on Neural Information Processing Systems (NeurIPS), 2024. [Acceptance Rate 25.8% ][arXiv]
[IC-14] Seonkyu Lim*, Jeongwhan Choi*, Noseong Park, Sang-Ha Yoon, Shinhyuck Kang, Young-Min Kim, and Hyunjoong Kang, "Bridging Dynamic Factor Models and Neural Controlled Differential Equations for Nowcasting GDP," In Proceedings of the 33rd ACM International Conference on Information and Knowledge Management (CIKM), 2024. [Applied Research Paper Acceptance rate: 32.59% (103/316) ][Paper][arXiv]
[IC-13] Jayoung Kim, Yehjin Shin, Jeongwhan Choi, Hyowon Wi, and Noseong Park, "Polynomial-based Self-Attention for Table Representation Learning", In International Conference on Machine Learning (ICML), 2024. [Acceptance Rate 27.5% (2610/9473)][arXiv]
[IC-12] Jeongwhan Choi, Sumin Park, Hyowon Wi, Sung-Bae Cho, and Noseong Park, "PANDA: Expanded Width-Aware Message Passing Beyond Rewiring," In International Conference on Machine Learning (ICML), 2024. [Acceptance Rate 27.5% (2610/9473)][Paper][arXiv]
[IC-11] Seoyoung Hong, Jeongwhan Choi, Yeon-Chang Lee, Srijan Kumar, Noseong Park, "SVD-AE: Simple Autoencoders for Collaborative Filtering," In International Joint Conference on Artificial Intelligence (IJCAI), 2024. [Acceptance Rate 14.00% (791/5651)][Paper][arXiv][Code]
[IC-10] Youn-Yeol Yu, Jeongwhan Choi, Woojin Cho, Kookjin Lee, Nayong Kim, Kiseok Chang, Chang-Seung Woo, Ilho Kim, Seok-Woo Lee, Joon-Young Yang, Sooyoung Yoon, and Noseong Park, "Learning Flexible Body Collision Dynamics with Hierarchical Contact Mesh Transformer," In International Conference on Learning Representations (ICLR), 2024. [Acceptance Rate 30.52% (2260/7404)][Paper][arXiv]
[IC-09] Yehjin Shin*, Jeongwhan Choi*, Hyowon Wi, Noseong Park, "An Attentive Inductive Bias for Sequential Recommendation Beyond the Self-Attention," In AAAI Conference on Artificial Intelligence (AAAI), 2024. [Acceptance Rate 23.75% (2342/12100)][Paper] [arXiv]
2023 (8 - IJ: 2, IC: 4, DJ:0, DC:1, W:1)
[IC-08] Seonkyu Lim, Jaehyeon Park, Seojin Kim, Hyowon Wi, Haksoo Lim, Jinsung Jeon, Jeongwhan Choi, and Noseong Park, "Long-term Time Series Forecasting based on Decomposition and Neural Ordinary Differential Equations," In IEEE International Conference on Big Data (Big Data), 2023. [Acceptance Rate 17.49% (92/526)][Paper]
[W-01] Jaehoon Lee, Chan Kim, Gyumin Lee, Haksoo Lim, Jeongwhan Choi, Kookjin Lee, Dongeun Lee, Sanghyun Hong and Noseong Park, "HyperNetwork Approximating Future Parameters for Time Series Forecasting under Temporal Drifts," NeurIPS 2023 Workshop on Distribution Shifts (DistShift), 2023. [Paper]
[IC-08] Jeongwhan Choi and Duksan Ryu, "QoS-Aware Graph Contrastive Learning for Web Service Recommendation", In Proceedings of the 30th Asia-Pacific Software Engineering Conference (APSEC), 2023. [Acceptance Rate 33.5%][arXiv]
[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][Code]
[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][Paper]
2022 (3 - IJ: 0, IC: 3, DJ:0, DC:0)
[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][Code][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][Code][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][Code][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)
[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. [arXiv] [Code] [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. [arXiv] [Code] [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)
[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)
[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.