Self-adaptive weights based on balanced residual decay rate for physics-informed neural networks and deep operator networks

Research article (Journal of Computational Physics, 2025) · cited 15× · AI/ML
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Self-adaptive weights based on balanced residual decay rate for physics-informed neural networks and deep operator networks

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Self-adaptive weights based on balanced residual decay rate for physics-informed neural networks and deep operator networks is a scholarly article[1].

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APA 4ort.xyz Knowledge Graph. (2026). Self-adaptive weights based on balanced residual decay rate for physics-informed neural networks and deep operator networks. Retrieved May 24, 2026, from https://4ort.xyz/entity/self-adaptive-weights-based-on-balanced-residual-decay-rate-for-physics-informed-neural-networks-and-deep-operator-netwo
MLA “Self-adaptive weights based on balanced residual decay rate for physics-informed neural networks and deep operator networks.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/self-adaptive-weights-based-on-balanced-residual-decay-rate-for-physics-informed-neural-networks-and-deep-operator-netwo.
BibTeX @misc{4ortxyz_self-adaptive-weights-based-on-balanced-residual-decay-rate-for-physics-informed-neural-networks-and-deep-operator-netwo_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Self-adaptive weights based on balanced residual decay rate for physics-informed neural networks and deep operator networks}}, year = {2026}, url = {https://4ort.xyz/entity/self-adaptive-weights-based-on-balanced-residual-decay-rate-for-physics-informed-neural-networks-and-deep-operator-netwo}, note = {Accessed: 2026-05-24}}
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