no code implementations • 28 May 2024 • Hyungtaik Oh, Wonkeun Jo, Dongil Kim
In this study, we propose an attention-based sequential recommendation method that employs multimodal data of items such as images, texts, and categories.
no code implementations • 22 May 2024 • Wonkeun Jo, Dongil Kim
Our proposed model, the Neural ForeCasting Layer (NFCL), employs a straightforward amalgamation of neural networks.
no code implementations • 20 May 2022 • Wonkeun Jo, Dongil Kim
By employing generalized additive models, the proposed NAM-NC successfully explains each input value's importance for multiple variables and time steps.
3 code implementations • 26 May 2019 • Doyup Lee, Suehun Jung, Yeongjae Cheon, Dongil Kim, Seungil You
TGNet learns an autoregressive model, conditioned on temporal contexts of forecasting targets from temporal-guided embedding.