Conferences

• Density of States Prediction of Crystalline Materials via Prompt-guided Multi-Modal Transformer
  Namkyeong Lee, Heewoong Noh, Sungwon Kim, Dongmin Hyun, Gyoung S. Na, Chanyoung Park
  NeurIPS, 2023
  [paper] [code]

• Muffin: Music Recommender System via Shuffle Invariant Training
  Yunhak Oh, Sukwon Yun, Dongmin Hyun, Sein Kim and Chanyoung Park
  CIKM, 2023
  [paper] [code]

• Conditional Graph Information Bottleneck for Molecular Relational Learning
  Namkyeong Lee, Dongmin Hyun, Gyoung S. Na, Sungwon Kim, Junseok Lee, and Chanyoung Park
  ICML, 2023
  [paper] [code]

• Mutual Enhancement of Long-Tailed User and Item for Sequential Recommendation
  Kibum Kim, Dongmin Hyun, Sukwon Yun, and Chanyoung Park
  SIGIR, 2023
  [paper] [code]

• Predicting Density of States via Multi-modal Transformer
  Namkyeong Lee, Heewoong Noh, Sungwon Kim, Dongmin Hyun, and Chanyoung Park
  ICLR Workshop on Machine Learning for Materials, 2023
  [paper] [code]

• Dynamic Multi-Behavior Sequence Modeling for Next Item Recommendation
  Junsu Cho, Dongmin Hyun, Dongwon Lim, Hyeonjae Chen, Hyoung-iel Park and Hwanjo Yu
  AAAI, 2023
  [paper] [code]

• Heterogeneous Graph Learning for Multi-modal Medical Data Analysis
  Sein Kim, Namkyeong Lee, Junseok Lee, Dongmin Hyun and Chanyoung Park
  AAAI, 2023
  [paper] [code]

• Generating Multiple-Length Summaries via Reinforcement Learning for Unsupervised Sentence Summarization
  Dongmin Hyun, Xiting Wang, Chayoung Park, Xing Xie and Hwanjo Yu
  EMNLP Findings, workshop on SustaiNLP 2022
  [paper] [code]

• Beyond Learning from Next Item: Sequential Recommendation via Personalized Interest Sustainability
  Dongmin Hyun, Chanyoung Park, Junsu cho and Hwanjo Yu
  CIKM, 2022
  [paper] [code]

• Relational Self-Supervised Representation Learning on Graphs
  Namkyeong Lee, Dongmin Hyun, Junseok Lee and Chanyoung Park
  CIKM, 2022
  [paper] [code]

• GraFN: Semi-Supervised Node Classification on Graph with Few Labels via Non-Parametric Distribution Assignment
  Junseok Lee, Yunhak Oh, Yeonjun In, Namkyeong Lee, Dongmin Hyun, Chanyoung Park
  SIGIR, 2022
  [paper] [code]

• Out-of-Category Document Identification Using Target-Category Names as Weak Supervision
  Dongha Lee, Dongmin Hyun, Jiawei Han and Hwanjo Yu
  ICDM short, 2021
  [paper] [code]

• Learning Heterogeneous Temporal Patterns for Timely Recommendation
  Junsu Cho, Dongmin Hyun, Seongku Kang and Hwanjo Yu
  WWW, 2021
  [paper] [code]

• Unsupervised Proxy Selection for Session-based Recommender Systems
  Junsu Cho, Seongku Kang, Dongmin Hyun and Hwanjo Yu
  SIGIR, 2021
  [paper] [code]

• Interest Sustainability-Aware Recommender System
  Dongmin Hyun, Junsu Cho, Chanyoung Park and Hwanjo Yu
  ICDM, 2020
  [paper] [code]

• Building Large-Scale Datasets for Aspect-Level Sentiment Analysis
  Dongmin Hyun, Junsu Cho and Hwanjo Yu
  COLING short, 2020
  [paper] [code]

• Review Sentiment-Guided Scalable Deep Recommender System
  Dongmin Hyun, Chanyoung Park, MinChul Yang, Ilhyeon Song, JungTae Lee, Hwanjo Yu
  SIGIR short, 2018
  [paper] [code]

Journals

• Deep single-cell RNA-seq data clustering with graph prototypical contrastive learning
  Junseok Lee, Sungwon Kim, Dongmin Hyun, Namkyeong Lee, Yejin Kim, and Chanyoung Park
  Bioinformatics (SCI), ICML 2023 Workshop on Computational Biology
  [paper] [code]

• Learning to Utilize Auxiliary Reviews for Recommendation
  Dongmin Hyun, Chanyoung Park, Junsu Cho and Hwanjo Yu
  Information Sciences, 2021 (SCI)
  [paper] [code]

• Target-Aware Convolutional Neural Network for Target-Level Sentiment Analysis
  Dongmin Hyun, Chanyoung Park, MinChul Yang, Ilhyeon Song, JungTae Lee, Hwanjo Yu
  Information Sciences, 2019 (SCI)
  [paper] [code]

• Influence Maximization Based on Reachability Sketches in Dynamic Graphs
  Dongeun Kim, Dongmin Hyun, Jinoh Oh, Wook-Shin Han and Hwanjo Yu
  Information Sciences, 2017 (SCI)
  [paper] [code]