1 code implementation • 15 Aug 2024 • Rujia Shen, Boran Wang, Chao Zhao, Yi Guan, Jingchi Jiang
Causal discovery from time-series data aims to capture both intra-slice (contemporaneous) and inter-slice (time-lagged) causality between variables within the temporal chain, which is crucial for various scientific disciplines.
no code implementations • 31 Jul 2024 • Liangliang Liu, Yi Guan, Boran Wang, Rujia Shen, Yi Lin, Chaoran Kong, Lian Yan, Jingchi Jiang
Imagining potential outcomes of actions before execution helps agents make more informed decisions, a prospective thinking ability fundamental to human cognition.
1 code implementation • 31 Jul 2024 • Rujia Shen, Yang Yang, Yaoxion Lin, Liangliang Liu, Boran Wang, Yi Guan, Jingchi Jiang
Time series forecasting (TSF) plays a crucial role in various applications, including medical monitoring and crop growth.
no code implementations • 3 Jun 2024 • Xuehui Yu, Yi Guan, Rujia Shen, Xin Li, Chen Tang, Jingchi Jiang
To tackle these issues, we introduce the Causal Prompting Reinforcement Learning (CPRL) framework, designed for highly suboptimal and resource-constrained online scenarios.
no code implementations • 23 May 2024 • Jingchi Jiang, Rujia Shen, Boran Wang, Yi Guan
We use the pre-trained CINN as a frozen introspective block of the RL agent, which integrates forward prediction and counterfactual inference to guide the policy updates, promoting more stable and safer BG control.
1 code implementation • 16 Oct 2020 • Sunny Verma, Jiwei Wang, Zhefeng Ge, Rujia Shen, Fan Jin, Yang Wang, Fang Chen, Wei Liu
In this research, we first propose a common network to discover both intra-modal and inter-modal dynamics by utilizing basic LSTMs and tensor based convolution networks.