Context-Driven Missing Data Imputation via Large Language Model
Lim, J, An, S., Woo, G., Kim, C., and Jeon J. J.
Publications.
Explore the lab’s papers and preprints by year, with links to publications and related resources.
↗
Estimating Subgraph Importance with Structural Prior Domain Knowledge
Kim, C., Jeon J. J., Woo, K. and An, S.
Balanced Marginal and Joint Distributional Learning for Tabular Data Synthesis via Mixture Cramer–Wold Distance
An, S., Hong, S. and Jeon J. J.
Large Scale Road-Traffic Noise Mapping with AI Technology
Choi, S., Park, T., Lim, J., Murphy E., and Jeon, J. J.
Generating High-Diversity Synthetic Tabular Data via Less-Constrained Prior
Park, S., Lim, J., Jeon J. J. and An, S.
Context-Aware Subgraph Explanations for Multi-Task GNNs
Yoon, Y., Kim, J., Choi, J. and Jeon J. J.
Uniform Pessimistic Risk and Optimal Portfolio
Hong, S. and Jeon J. J.
On the Identifiability of Subgraph Explanations in Self-Explainable GNNs
Cho, S. and Jeon J. J.
CTDKG: Towards Uncovering Chemical–Gene–Disease Pathways via Knowledge Graphs
Cho, S., Woo, G., Lim, J., Kim, C, Hong S., and Jeon J. J.
Variational Inference for Dynamic Mixtures in Probabilistic Time-Series Forecasting
An, S., Hong, S. and Jeon J. J.
ProDA: Projection-based Distribution Alignment for Deep Time Series Forecasting
Lim, J., An, S., and Jeon J. J.
Recovering Task Intents in Unified LLM-based Dialogue via Candidate Response Selection
Kim, J. Yoon, Y., Lim, J., and Jeon J. J.
Embedding-Based Query Performance Prediction from Retriever-Generated Embeddings
Jung, J., Jeong, D., and Jeon J. J.
Hawkes-Driven Popularity-Aware Sampling for Contrastive Recommendation Learning
Shin, W. Sakurai, K., Ogawa, T and Jeon J. J.
Modeling and Debiasing Temporal Popularity in Recommendation with Counting Processes
Shin, W., Sakurai, K., Ogawa, T and Jeon J. J.
Masked Language Modeling Becomes Conditional Density Estimation for Tabular Data Synthesis
An, S., Woo, G., Shin, W., Kim, K., Kim, D., Choi, J., and Jeon J. J.