PINA and PSO-PINN
PINA is a general-purpose PINN framework while PSO-PINN is a specialized optimization variant, making them competitors for the same use case (training physics-informed neural networks) rather than complementary tools.
About PINA
mathLab/PINA
Physics-Informed Neural networks for Advanced modeling
This tool helps scientists and engineers build predictive models that adhere to known physical laws or integrate with existing data. You input your scientific problem, including any governing equations or experimental data, and it outputs a trained neural network that can simulate complex systems or make predictions while respecting physics. It's designed for researchers, computational scientists, and anyone working with scientific data and simulations.
About PSO-PINN
caio-davi/PSO-PINN
Physics-Informed Neural Networks Trained with Particle Swarm Optimization
This project helps engineers and scientists more accurately solve complex physics problems modeled by partial differential equations using deep learning. It takes in your differential equation model and relevant data, and outputs a robust, more reliable solution with quantified uncertainty. Researchers and practitioners in fields like fluid dynamics, heat transfer, or materials science who use Physics-Informed Neural Networks (PINNs) will find this useful.
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