#physics-informed networks

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Stories, products and papers tagged "physics-informed networks", newest first.

Sep 17

Interpretable Patch-Based Deep Learning for Wildfire Spread Prediction

This research provides a detailed comparison of different deep learning architectures for wildfire prediction, which could be useful for anyone working on or interested in the application of AI for disaster management.

#deep learning #physics-informed networks

arXiv cs.AI@Marcin Lawenda et al. (5)Source

Jul 23

Models12:27

Chinese contentPG-KINN：基于物理信息的Petrov-Galerkin KAN网络求解正反PDE

PG-KINN用Petrov-Galerkin方法结合KAN，在多个力学难题上精度超过PIKAN和MLP，值得做计算力学的人试试。

#PG-KINN #KAN #partial differential equations #physics-informed networks

arXiv cs.LG@Amirhossein Sadr et al. (6)Source

Jun 10

PapersSelected09:25

Chinese contentLSTM-GNN 耦合框架实现非线性力学场重建，加速多尺度仿真

做多尺度仿真和材料力学计算的团队，终于有了一个能同时处理时间依赖和空间应力场的高效替代方案——比有限元快 1000 倍，还能跨网格直接迁移，建议做结构分析的开发者点开看看。

#LSTM #graph neural networks #physics-informed networks

arXiv cs.LG@Manuel Ricardo Guevara Garban et al. (6)Source

May 19

PapersSelected11:02

Chinese contentUTOPYA：多模态深度学习框架用于物理信息异常检测与时间序列预测

UTOPYA为工业过程监控提供了首个融合物理信息与多模态数据的端到端方案，做异常检测和过程控制的工程师可以直接参考其架构设计，尤其适合数据稀缺场景下的部署决策。

#anomaly detection #multimodal fusion #physics-informed networks #time series forecasting

arXiv cs.LG@Robson W. S. Pessoa et al. (4)Source