Weather and climate modelling with neural differential equations

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Overview

This is a new direction for the lab – more to come!

Multi-scale simulation with physics-informed neural networks

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… Read more →
SciML-enhanced planetary exploration: advancing lunar and martian imaging

Overview Scientists and engineers leading missions like NASA’s Artemis program and future Mars expeditions, along with planetary researchers studying our solar system’s evolution, rely heavily… Read more →
Machine learning with geodesic flows

Overview Many physical, biological and engineering systems evolve over time according to geometric laws, for example planets follow elliptical orbits shaped by gravity, and fluids… Read more →
Efficient and differentiable population balance modelling with JAX

Overview Population balance equations (PBEs) are used to model the evolution of populations of particles over time, such as in crystallisation processes, chemical reactors, and… Read more →
Extending quantum theories with AI

Overview Quantum theory is incredibly powerful for predicting the probabilities of what we’ll see in experiments, but it cannot tell us the certain outcome of… Read more →
Weather and climate modelling with neural differential equations

Overview This is a new direction for the lab – more to come! Team & collaborators Read more →