1 citations · 1 across the 1 of their papers we have counts for
2 papers
physics.comp-ph2022★ 1 cited
Learning Feynman Diagrams using Graph Neural Networks
Harrison Mitchell, Alexander Norcliffe, Pietro Liò
In the wake of the growing popularity of machine learning in particle physics, this work finds a new application of geometric deep learning on Feynman diagrams to make accurate and…
cs.LG2021
Meta-learning using privileged information for dynamics
Ben Day, Alexander Norcliffe, Jacob Moss +1
Neural ODE Processes approach the problem of meta-learning for dynamics using a latent variable model, which permits a flexible aggregation of contextual information. This flexibil…