Tag: Simulation
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Multi-scale simulation with physics-informed neural networks
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Overview Physics-informed neural networks (PINNs) have emerged as a promising tool for solving differential equations. They have been applied to many scientific problems and a large number of approaches extending their capabilities have been proposed. PINNs work by using a neural network to directly approximate the solution and training it to satisfy the differential equation.…
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Weather and climate modelling with neural differential equations
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Overview This is a new direction for the lab – more to come! Team & collaborators