PyKale: Knowledge-Aware Machine Learning from Multiple Sources in Python

1 code implementation • 17 Jun 2021 • Haiping Lu, Xianyuan Liu, Robert Turner, Peizhen Bai, Raivo E Koot, Shuo Zhou, Mustafa Chasmai, Lawrence Schobs

Machine learning is a general-purpose technology holding promises for many interdisciplinary research problems.

BIG-bench Machine Learning Dimensionality Reduction +3

Uncertainty Estimation for Heatmap-based Landmark Localization

2 code implementations • 4 Mar 2022 • Lawrence Schobs, Andrew J. Swift, Haiping Lu

We propose Quantile Binning, a data-driven method to categorize predictions by uncertainty with estimated error bounds.

Tensor-based Multimodal Learning for Prediction of Pulmonary Arterial Wedge Pressure from Cardiac MRI

1 code implementation • 14 Mar 2023 • Prasun C. Tripathi, Mohammod N. I. Suvon, Lawrence Schobs, Shuo Zhou, Samer Alabed, Andrew J. Swift, Haiping Lu

In this work, we develop a tensor learning-based pipeline for identifying PAWP from multimodal cardiac Magnetic Resonance Imaging (MRI).