1 citations · 1 across the 3 of their papers we have counts for
3 papers
Diffusion-Augmented Neural Processes
Lorenzo Bonito, James Requeima, Aliaksandra Shysheya +1
Over the last few years, Neural Processes have become a useful modelling tool in many application areas, such as healthcare and climate sciences, in which data are scarce and predi…
Sim2Real for Environmental Neural Processes
Jonas Scholz, Tom R. Andersson, Anna Vaughan +2
Machine learning (ML)-based weather models have recently undergone rapid improvements. These models are typically trained on gridded reanalysis data from numerical data assimilatio…
Challenges and Pitfalls of Bayesian Unlearning
Ambrish Rawat, James Requeima, Wessel Bruinsma +1
Machine unlearning refers to the task of removing a subset of training data, thereby removing its contributions to a trained model. Approximate unlearning are one class of methods…