Sliding physical invariant neural operator for long-term prediction of complex dynamics in physical systems. [PDF]
Wang Y, Li Y, Peng Y, Ying S.
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Automatic network structure discovery of physics informed neural networks via knowledge distillation. [PDF]
Liu Z +6 more
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AI-driven predictive modelling of residual stress of HVOF thermal sprayed carbon-based composite coatings using physics-informed neural networks. [PDF]
Tyagi A, Dadhich A, Sirohi S, Gupta AK.
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Accurate and scalable deep Maxwell solvers. [PDF]
Mao C, Fan JA.
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WF-PINNs: solving forward and inverse problems of burgers equation with steep gradients using weak-form physics-informed neural networks. [PDF]
Wang X, Yi S, Gu H, Xu J, Xu W.
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Two-stage ROM: a hybrid reduced order model for offline and online efficiency. [PDF]
Dhopeshwar R, Bansal H, Veroy K.
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A primer on variational inference for physics-informed deep generative modelling. [PDF]
Glyn-Davies A +4 more
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Sparse identification of nonlinear dynamics and Koopman operators with Shallow Recurrent Decoder Networks. [PDF]
Gao ML, Williams JP, Kutz JN.
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Deterministic, stochastic, and mean-field PDE models in neuroscience. [PDF]
Çetin C +5 more
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