2 papers
cs.LG2024
FedFixer: Mitigating Heterogeneous Label Noise in Federated Learning
Xinyuan Ji, Zhaowei Zhu, Wei Xi +4
Federated Learning (FL) heavily depends on label quality for its performance. However, the label distribution among individual clients is always both noisy and heterogeneous. The h…
physics.flu-dyn2023
Continuous and discontinous compressible flows in a converging-diverging channel solved by physics-informed neural networks without data
Liang Hong, Song Zilong, Zhao Chong +1
Physics-informed neural networks (PINNs) are employed to solve the classical compressible flow problem in a converging-diverging nozzle. This problem represents a typical example d…