Physical Activation Functions (PAFs): An Approach for More Efficient
Induction of Physics into Physics-Informed Neural Networks (PINNs)

Physical Activation Functions (PAFs): An Approach for More Efficient Induction of Physics into Physics-Informed Neural Networks (PINNs)

29 May 2022

Paal Ostebo Andersen

Papers citing "Physical Activation Functions (PAFs): An Approach for More Efficient Induction of Physics into Physics-Informed Neural Networks (PINNs)"

8 / 8 papers shown

Title
Plane-Wave Decomposition and Randomised Training; a Novel Path to Generalised PINNs for SHM Rory Clements James Ellis Geoff Hassall Simon Horsley Gavin Tabor 45 0 0 31 Mar 2025
Challenges and Advancements in Modeling Shock Fronts with Physics-Informed Neural Networks: A Review and Benchmarking Study J. Abbasi Ameya D. Jagtap Ben Moseley Aksel Hiorth P. Andersen PINN AI4CE 31 1 0 14 Mar 2025
One-shot backpropagation for multi-step prediction in physics-based system identification -- EXTENDED VERSION Cesare Donati Martina Mammarella Fabrizio Dabbene C. Novara C. Lagoa 11 2 0 31 Oct 2023
About optimal loss function for training physics-informed neural networks under respecting causality V. A. Es'kin Danil V. Davydov Ekaterina D. Egorova Alexey O. Malkhanov Mikhail A. Akhukov Mikhail E. Smorkalov PINN 8 6 0 05 Apr 2023
Mixed formulation of physics-informed neural networks for thermo-mechanically coupled systems and heterogeneous domains Ali Harandi Ahmad Moeineddin Michael Kaliske Stefanie Reese Shahed Rezaei AI4CE PINN 18 42 0 09 Feb 2023
Neural Networks with Physics-Informed Architectures and Constraints for Dynamical Systems Modeling Franck Djeumou Cyrus Neary Eric Goubault S. Putot Ufuk Topcu PINN AI4CE 32 67 0 14 Sep 2021
Parallel Physics-Informed Neural Networks via Domain Decomposition K. Shukla Ameya Dilip Jagtap George Karniadakis PINN 98 272 0 20 Apr 2021
Machine Learning and Big Scientific Data Tony (Anthony) John Grenville Hey K. Butler Sam Jackson Jeyarajan Thiyagalingam AI4CE 20 74 0 12 Oct 2019