2 citations · 3 across the 2 of their papers we have counts for
2 papers
cs.LG2023★ 2 cited
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…
cs.LG2023★ 1 cited
Physics-Inspired Interpretability Of Machine Learning Models
Maximilian P Niroomand, David J Wales
The ability to explain decisions made by machine learning models remains one of the most significant hurdles towards widespread adoption of AI in highly sensitive areas such as med…