| TimeKit: A time-series forecasting-based upgrade kit for collaborative filtering S Hong, M Jo, S Kook, J Jung, H Wi, N Park, SB Cho 2022 IEEE International Conference on Big Data (Big Data), 565-574, 2022 | 2 | 2022 |
| An attentive inductive bias for sequential recommendation beyond the self-attention Y Shin, J Choi, H Wi, N Park Proceedings of the AAAI Conference on Artificial Intelligence 38 (8), 8984-8992, 2024 | 1 | 2024 |
| RDGCL: Reaction-Diffusion Graph Contrastive Learning for Recommendation J Choi, H Wi, C Lee, SB Cho, D Lee, N Park arXiv preprint arXiv:2312.16563, 2023 | 1 | 2023 |
| Graph Convolutions Enrich the Self-Attention in Transformers! J Choi, H Wi, J Kim, Y Shin, K Lee, N Trask, N Park arXiv preprint arXiv:2312.04234, 2023 | 1 | 2023 |
| Stochastic Sampling for Contrastive Views and Hard Negative Samples in Graph-based Collaborative Filtering C Lee, J Choi, H Wi, SB Cho, N Park arXiv preprint arXiv:2405.00287, 2024 | | 2024 |
| Continuous-time Autoencoders for Regular and Irregular Time Series Imputation H Wi, Y Shin, N Park Proceedings of the 17th ACM International Conference on Web Search and Data …, 2024 | | 2024 |
| Long-term Time Series Forecasting based on Decomposition and Neural Ordinary Differential Equations S Lim, J Park, S Kim, H Wi, H Lim, J Jeon, J Choi, N Park 2023 IEEE International Conference on Big Data (BigData), 748-757, 2023 | | 2023 |
