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20242026
most citedUncertainty Quantification of Graph Convolution Neural Network Models of Evolving Processes

3 citations · 6 across the 7 of their papers we have counts for

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cs.LG2026

Interval and fuzzy physics-augmented neural networks (iPANN and fPANN) for uncertainty quantification and propagation in constitutive modeling

Somesh Pratap Singh, Govinda Anantha Padmanabha, Jingye Tan +4

Constitutive modeling under uncertainty remains a central challenge for reliable mechanics simulations, particularly when the available stress-deformation data are sparse, noisy, o…