2 citations · 5 across the 4 of their papers we have counts for
3 papers · 1 filter
Refining embeddings with fill-tuning: data-efficient generalised performance improvements for materials foundation models
Matthew P. Wilson, Edward O. Pyzer-Knapp, Nicolas Galichet +1
Pretrained foundation models learn embeddings that can be used for a wide range of downstream tasks. These embeddings optimise general performance, and if insufficiently accurate a…
Evolution of -means solution landscapes with the addition of dataset outliers and a robust clustering comparison measure for their analysis
Luke Dicks, David J. Wales
The -means algorithm remains one of the most widely-used clustering methods due to its simplicity and general utility. The performance of -means depends upon location of mini…
Physics Inspired Approaches To Understanding Gaussian Processes
Maximilian P. Niroomand, Luke Dicks, Edward O. Pyzer-Knapp +1
Prior beliefs about the latent function to shape inductive biases can be incorporated into a Gaussian Process (GP) via the kernel. However, beyond kernel choices, the decision-maki…