4 papers
A unified framework for equation discovery and dynamic prediction of hysteretic systems
Siyuan Yang, Wei Liu, Zhilu Lai
Hysteresis is a nonlinear phenomenon with memory effects, where a system's output depends on both its current state and past states. It is prevalent in various physical and mechani…
Let the Abyss Stare Back Adaptive Falsification for Autonomous Scientific Discovery
Peiran Li, Fangzhou Lin, Shuo Xing +5
Autonomous scientific discovery is entering a more dangerous regime: once the evaluator is frozen, a sufficiently strong search process can learn to win the exam without learning t…
KP-PINNs: Kernel Packet Accelerated Physics Informed Neural Networks
Siyuan Yang, Cheng Song, Zhilu Lai +1
Differential equations are involved in modeling many engineering problems. Many efforts have been devoted to solving differential equations. Due to the flexibility of neural networ…
Transforming physics-informed machine learning to convex optimization
Letian Yi, Siyuan Yang, Ying Cui +1
Physics-Informed Machine Learning (PIML) offers a powerful paradigm of integrating data with physical laws to address important scientific problems, such as parameter estimation, i…