4 papers
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…
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…
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…