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2025年2月7日 · We propose compleX-PINN, a novel physics-informed neural network (PINN) architecture that incorporates a learnable activation function inspired by Cauchy integral …

2024年2月7日 · 物理信息神经网络（Physics-Informed Neural Networks，简称PINN）是一种结合了深度学习和物理学知识的机器学习模型。 与传统的数据驱动的神经网络不同，PINNs 在学 …

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There is a growing consensus that physics-informed neural networks (PINNs) can address these concerns by integrating physics-informed (PI) rules or laws into state-of-the-art DL …

2024年8月3日 · PINN是将物理定律嵌入深度学习框架，约束神经网络训练的新型方法。特别适用于解决AI交叉学科中复杂的偏微分方程。可以说，PINN能够大大降低实验难度，让你更容易 …

2022年11月21日 · Physics-informed neural networks (PINNs) [1] are frequently employed to address a variety of scientific computer problems. Due to their superior approximation and …

Physics-informed neural network (PINN) has recently gained increasing interest in computational mechanics. This work extends the PINN to computational solid mechanics problems. Our …