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gr-qc2026
Binary Black Hole Puncture Initial Data with Physics-Informed Neural Networks
Thiago Assumpção, Ignacio Brevis, Irene Pitsiladi +2
We present Pinndorama, a physics-informed neural network (PINN) code for solving the Hamiltonian constraint in the puncture formalism. The networks are trained solely on the govern…
math.NA2026
Neural network approximation in discrete dual norms with adaptive test spaces
Tanakorn Udomworarat, Ignacio Brevis, Kristoffer G. van der Zee +1
In robust variational physics-informed neural networks (RVPINNs), the loss function is formulated in terms of the Riesz representative of the variational residual within a discrete…