Weihua Deng — accepted AI-conference papers

2025

Efficient Training of Neural Fractional-Order Differential Equation via Adjoint Backpropagation

Qiyu Kang, Xuhao Li, Kai Zhao, Wenjun Cui, Yanan Zhao, Weihua Deng +1

AAAI 2025technical

Fractional-order differential equations (FDEs) enhance traditional differential equations by extending the order of differential operators from integers to real numbers, offering greater flexibility in modeling complex dynamic systems with nonlocal characteristics. Recent progress at the intersectio…

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2025

Neural Variable-Order Fractional Differential Equation Networks

Wenjun Cui, Qiyu Kang, Xuhao Li, Kai Zhao, Wee Peng Tay, Weihua Deng +1

AAAI 2025technical

The use of neural differential equation models in machine learning applications has gained significant traction in recent years. In particular, fractional differential equations (FDEs) have emerged as a powerful tool for capturing complex dynamics in various domains. While existing models have prima…

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