SAMSGL: Series-Aligned Multi-Scale Graph Learning for Spatio-Temporal Forecasting

no code implementations • 5 Dec 2023 • Xiaobei Zou, Luolin Xiong, Yang Tang, Jurgen Kurths

Despite the significant strides made by graph-based networks in spatio-temporal forecasting, there remain two pivotal factors closely related to forecasting performance that need further consideration: time delays in propagation dynamics and multi-scale high-dimensional interactions.

Graph Learning Graph structure learning +3

Interpretable Deep Reinforcement Learning for Optimizing Heterogeneous Energy Storage Systems

no code implementations • 20 Oct 2023 • Luolin Xiong, Yang Tang, Chensheng Liu, Shuai Mao, Ke Meng, ZhaoYang Dong, Feng Qian

ESS operators can reap benefits from energy arbitrage by optimizing operations of storage equipment.

Decision Making reinforcement-learning +1

Hybrid Control Policy for Artificial Pancreas via Ensemble Deep Reinforcement Learning

no code implementations • 13 Jul 2023 • Wenzhou Lv, Tianyu Wu, Luolin Xiong, Liang Wu, Jian Zhou, Yang Tang, Feng Qian

Objective: The artificial pancreas (AP) has shown promising potential in achieving closed-loop glucose control for individuals with type 1 diabetes mellitus (T1DM).

Meta-Learning Model Predictive Control +1

Molecular Joint Representation Learning via Multi-modal Information

no code implementations • 25 Nov 2022 • Tianyu Wu, Yang Tang, Qiyu Sun, Luolin Xiong

To further fusing such multi-modal imformation, the correspondence between learned chemical feature from different representation should be considered.

Drug Discovery molecular representation +2