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A 2 hour workshop I organised to bring physics PhD students up to speed with modern machine learning.
Extending neural cellular automata to learn spatiotemporal dynamics
Published in PLOS Computational Biology, 2024
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Recommended citation: Alex D. Richardson, Richard A Blythe, Tibor Antal, Linus J. Schumacher. "Learning spatio-temporal patterns with Neural Cellular Automata." PLOS Computational Biology. https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1011589
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International Centre for Mathematical Sciences workshop on the individual and collective behaviour in biological and robotic systems. More information
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European Conference on Mathematical and Theoretical Biology. More information
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Winter school on mathematical techniques for studying self organising systems. Focused mostly on Vicsek model like PDEs. More information
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Conference on the intersection between non-equilibrium physics, complex systems and biology. More information
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International Centre for Mathematical Sciences workshop on the Mathematical Foundations of Data Driven Engineering. More information
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Short conference on a wide range of mathematical biology where seperations of timescales are important. More information
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Conference on deep learning for computational physics. More information
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Winter school on physics of life. Focused mostly on advances in imaging techniques, and on soft skills training. More information
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Workshop on Dynamics, Data and Deep Learning More information
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Hackathon exploring generative AI, organised by the Isaac Newton Institute and Amazon. More information
Undergraduate course, University of Edinburgh, School of Physics and Astronomy, 2022
I was a teaching assitant on an undergraduate physics course teaching scientific programming techniques. This included numerical linear algebra; regression and optimisation; and numerical methods for differential equations.
Undergraduate course, Unviersity of Edinburgh, School of Physics and Astronomy, 2023
I was a teaching assistant on an undergraduate physics course teaching advanced simulation and visualisation techniques. This course explored Ising models, cellular automata, epidemiology modelling and numerical PDEs. There was also a focus on interpretting and visualising outputs of simulations.