PUBLICATIONS

Working Papers

• Chanyeong Kim, Heejin Kim, and Weonyoung Joo*. Mixed-Effect Neural Processes for Multi-Annotator Semi-Supervised Medical Image Segmentation. Work in Progress.

• Jiwon Park, Sooyeon Kim, and Weonyoung Joo*. De-Biased Controllable Text Generation with Classifier-Guided Rectified Flow Language Model. Work in Progress.

• Sunkyung Lee, Heejin Kim, Sooyeon Kim, and Weonyoung Joo*. Kernel-Dispersing Diffusion Sampling. Work in Progress.

• Rosy Oh, Kyungbae Park*, Weonyoung Joo*, and Jae Youn Ahn*. Generalized Laplace Approximation and Its Application to Credibility Method. Under Review.

• Dongjun Kim, Seungjae Shin, Kyungwoo Song, Il-Chul Moon, and Weonyoung Joo*. Adversarial Likelihood-Free Inference on Black-Box Generator. Work in Progress.

(*: As a (Co-)Corresponding Author, ^: Equal Contribution)

Journal Publications

• Weonyoung Joo*, Dongjun Kim, Seungjae Shin, and Il-Chul Moon. Generalized Gumbel-Softmax Gradient Estimator for Generic Discrete Random Variables. Pattern Recognition Letters, Volume 196, 148-155. 2025.

• Dongjun Kim, Kyungwoo Song, Seungjae Shin, Wanmo Kang, Il-Chul Moon, and Weonyoung Joo*. Sequential Neural Joint Estimation for Likelihood-Free Inference. Journal of the Korean Statistical Society, Volume 54, 858-887. 2025.

• Dongyeol Lee, Weonyoung Joo*, and Woo Chang Kim*. Impact of Changes in Benchmark Constituents on Portfolio Delegation. Industrial Engineering and Management Systems, Volume 24 (1), 42-50. 2025.

• Jieon Lim and Weonyoung Joo*. Counterfactual Image Generation by Disentangling Data Attributes with Deep Generative Model. Communications for Statistical Applications and Methods, Volume 30 (6), 589-603. 2023.

• Dongjun Kim, Kyungwoo Song, Yoon-Yeong Kim, Yongjin Shin, Wanmo Kang, Il-Chul Moon, and Weonyoung Joo*. Sequential Likelihood-Free Inference with Neural Proposal. Pattern Recognition Letters, Volume 169, 102-109. 2023.

• Sungeun Kim, Mingi Ji, Il-Chul Moon, and Weonyoung Joo*. Welfare Program Recommendation by Conditional Variational Autoencoder and Collaborative Filtering. Journal of the Korean Institute of Industrial Engineers, Volume 49 (1), 28-36. 2023.

• Hyeongwoo Kong, Wonje Yun, Weonyoung Joo, Ju‐Hyun Kim, Kyoung‐Kuk Kim, Il‐Chul Moon, and Woo Chang Kim. Constructing Personalized Recommender System for Life Insurance Products with Machine Learning Techniques. Intelligent Systems in Accounting, Finance and Management, Volume 29 (4), 242-253. 2022.

• Weonyoung Joo, Wonsung Lee, Sungrae Park, and Il-Chul Moon. Dirichlet Variational Autoencoder. Pattern Recognition, Volume 107, 107514. 2020.

• Ilkyoo Choi^, Weonyoung Joo^, and Minki Kim^. The Layer Number of α-Evenly Distributed Point Sets. Discrete Mathematics, Volume 343 (10), 112029. 2020.

(*: As a (Co-)Corresponding Author, ^: Equal Contribution)

Conference Publications

• Youngjae Cho, HeeSun Bae, Seungjae Shin, Yeo Dong Youn, Weonyoung Joo, and Il-Chul Moon. Make Prompts Adaptable: Bayesian Modeling for Vision-Language Prompt Learning with Data-Dependent Prior. AAAI Conference on Artificial Intelligence (AAAI). 2024.

• Seungjae Shin^, Heesun Bae^, Donghyeok Shin, Weonyoung Joo, and Il-Chul Moon. Loss Curvature Matching for Dataset Selection and Condensation. International Conference on Artificial Intelligence and Statistics Conference (AISTATS). 2023.

• Hyemi Kim, Seungjae Shin, JoonHo Jang, Kyungwoo Song, Weonyoung Joo, Wanmo Kang, and Il-Chul Moon. Counterfactual Fairness with Disentangled Causal Effect Variational Autoencoder. AAAI Conference on Artificial Intelligence (AAAI). 2021.

• Seungjae Shin, Kyungwoo Song, JoonHo Jang, Hyemi Kim, Weonyoung Joo, and Il-Chul Moon. Neutralizing Gender Bias in Word Embedding with Latent Disentanglement and Counterfactual Generation. Findings of the Association for Computational Linguistics: Conference on Empirical Methods in Natural Language Processing (Findings of EMNLP). 2020.

• Byeonghu Na, Hyemi Kim, Kyungwoo Song, Weonyoung Joo, Yoon-Yeong Kim, and Il-Chul Moon. Deep Generative Positive-Unlabeled Learning under Selection Bias. International Conference on Information and Knowledge Management (CIKM). 2020.

• Mingi Ji, Weonyoung Joo, Kyungwoo Song, Yoon-Yeong Kim, and Il-Chul Moon. Sequential Recommendation with Relation-Aware Kernelized Self-Attention. AAAI Conference on Artificial Intelligence (AAAI). 2020.

• Wonsung Lee, Sungrae Park, Weonyoung Joo, and Il-Chul Moon. Diagnosis Prediction via Medical Context Attention Networks Using Deep Generative Modeling. IEEE International Conference on Data Mining (ICDM). 2018.

(*: As a (Co-)Corresponding Author, ^: Equal Contribution)