| 2026 | AAAI | COGS: A Causal Representation Learning Framework for Out-of-Distribution Generalization in Time Series. | Xinxin Song, Yuxiao Cheng, Tingxiong Xiao, Jinli Suo |
| 2025 | AAAI | A Compact Implicit Neural Representation for Efficient Storage of Massive 4D Functional Magnetic Resonance Imaging. | Ruoran Li, Runzhao Yang, Wenxin Xiang, Yuxiao Cheng, Tingxiong Xiao, Lu Yang, Jinli Suo |
| 2025 | AAAI | FIND: A Framework for Discovering Formulas in Data. | Tingxiong Xiao, Yuxiao Cheng, Jinli Suo |
| 2024 | AAAI | CUTS+: High-Dimensional Causal Discovery from Irregular Time-Series. | Yuxiao Cheng, Lianglong Li, Tingxiong Xiao, Zongren Li, Jinli Suo, Kunlun He, Qionghai Dai |
| 2024 | AAAI | SHoP: A Deep Learning Framework for Solving High-Order Partial Differential Equations. | Tingxiong Xiao, Runzhao Yang, Yuxiao Cheng, Jinli Suo |
| 2024 | ICLR | CausalTime: Realistically Generated Time-series for Benchmarking of Causal Discovery. | Yuxiao Cheng, Ziqian Wang, Tingxiong Xiao, Qin Zhong, Jinli Suo, Kunlun He |
| 2023 | AAAI | SCI: A Spectrum Concentrated Implicit Neural Compression for Biomedical Data. | Runzhao Yang, Tingxiong Xiao, Yuxiao Cheng, Qianni Cao, Jinyuan Qu, Jinli Suo, Qionghai Dai |
| 2023 | ICLR | CUTS: Neural Causal Discovery from Irregular Time-Series Data. | Yuxiao Cheng, Runzhao Yang, Tingxiong Xiao, Zongren Li, Jinli Suo, Kunlun He, Qionghai Dai |