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cs.LG2026
Beyond Linear Dynamics: Neural Bilinear Dynamical Models for Time Series Forecasting
Mengzhou Gao, Huangqian Yu, Pengfei Jiao
Time series in real-world applications are often generated by nonlinear dynamical systems, making accurate forecasting challenging. Existing approaches that explicitly model system…
cs.LG2026
One-Step Graph-Structured Neural Flows for Irregular Multivariate Time Series Classification
Mengzhou Gao, Kaiwei Wang, Pengfei Jiao
Neural Flows efficiently model irregular multivariate time series by directly learning ODE solution trajectories with neural networks, bypassing step-by-step numerical solvers. Des…
cs.LG2026
Towards OOD Generalization in Dynamic Graphs via Causal Invariant Learning
Xinxun Zhang, Pengfei Jiao, Mengzhou Gao +2
Although dynamic graph neural networks (DyGNNs) have demonstrated promising capabilities, most existing methods ignore out-of-distribution (OOD) shifts that commonly exist in dynam…