| Coagulant dosage determination using deep learning-based graph attention multivariate time series forecasting model S Lin, J Kim, C Hua, MH Park, S Kang Water Research 232, 119665, 2023 | 10 | 2023 |
| RL4CO: a Unified Reinforcement Learning for Combinatorial Optimization Library F Berto, C Hua, J Park, M Kim, H Kim, J Son, H Kim, J Kim, J Park Advances in Neural Information Processing Systems, NeurIPS 2023 Workshop …, 2023 | 7* | 2023 |
| Comparing artificial and deep neural network models for prediction of coagulant amount and settled water turbidity: Lessons learned from big data in water treatment operations S Lin, J Kim, C Hua, S Kang, MH Park Journal of Water Process Engineering 54, 103949, 2023 | 7 | 2023 |
| Evolvehypergraph: Group-aware dynamic relational reasoning for trajectory prediction J Li, C Hua, J Park, H Ma, V Dax, MJ Kochenderfer arXiv preprint arXiv:2208.05470, 2022 | 3 | 2022 |
| Efficient Continuous Spatio-Temporal Simulation with Graph Spline Networks C Hua, F Berto, M Poli, S Massaroli, J Park International Conference on Machine Learning, ICML 2022 Workshop: AI for Science, 2022 | 3 | 2022 |
| HiMAP: Learning Heuristics-Informed Policies for Large-Scale Multi-Agent Pathfinding H Tang, F Berto, Z Ma, C Hua, K Ahn, J Park arXiv preprint arXiv:2402.15546, 2024 | 1 | 2024 |
| Optimizing coagulant dosage using deep learning models with large-scale data J Kim, C Hua, K Kim, S Lin, G Oh, MH Park, S Kang Chemosphere 350, 140989, 2024 | 1 | 2024 |
| Multi-Agent Dynamic Relational Reasoning for Social Robot Navigation J Li, C Hua, H Ma, J Park, V Dax, MJ Kochenderfer arXiv preprint arXiv:2401.12275, 2024 | 1 | 2024 |
| Learning Efficient Surrogate Dynamic Models with Graph Spline Networks C Hua, F Berto, M Poli, S Massaroli, J Park Advances in Neural Information Processing Systems, NeurIPS 2023, 2023 | | 2023 |
Jinkyoo ParkDepartment of Industrial and Systems Engineering, KAISTVerified email at kaist.ac.kr
