| Infograph: Unsupervised and semi-supervised graph-level representation learning via mutual information maximization FY Sun, J Hoffmann, V Verma, J Tang ICLR 2020 (spotlight), 2019 | 71 | 2019 |
| A memory-network based solution for multivariate time-series forecasting YY Chang, FY Sun, YH Wu, SD Lin arXiv preprint arXiv:1809.02105, 2018 | 22 | 2018 |
| vGraph: A Generative Model for Joint Community Detection and Node Representation Learning FY Sun, M Qu, J Hoffmann, CW Huang, J Tang NeurIPS'19, 2019 | 17 | 2019 |
| Designing Non-greedy Reinforcement Learning Agents with Diminishing Reward Shaping FY Sun, YY Chang, YH Wu, SD Lin Proceedings of the 2018 AAAI/ACM Conference on AI, Ethics, and Society, 297-302, 2018 | 6 | 2018 |
| ANS: adaptive network scaling for deep rectifier reinforcement learning models YH Wu, FY Sun, YY Chang, SD Lin arXiv preprint arXiv:1809.02112, 2018 | 2 | 2018 |
| A Regulation Enforcement Solution for Multi-agent Reinforcement Learning FY Sun, YY Chang, YH Wu, SD Lin Proceedings of the 18th International Conference on Autonomous Agents and …, 2019 | 1 | 2019 |
| Put Chatbot into Its Interlocutor's Shoes: New Framework to Learn Chatbot Responding with Intention H Su, JH Jhan, F Sun, S Sahay, H Lee arXiv preprint arXiv:2103.16429, 2021 | | 2021 |
| Organ At Risk Segmentation with Multiple Modality KL Tseng, W Hsu, C Wu, YF Shih, FY Sun arXiv preprint arXiv:1910.07800, 2019 | | 2019 |
Jordan HoffmannResearch Scientist, DeepMindZweryfikowany adres z google.com
