3 papers
cs.LG2025
Density-Aware Farthest Point Sampling
Paolo Climaco, Jochen Garcke
We focus on training machine learning regression models in scenarios where the availability of labeled training data is limited due to computational constraints or high labeling co…
cs.LG2023
On minimizing the training set fill distance in machine learning regression
Paolo Climaco, Jochen Garcke
For regression tasks one often leverages large datasets for training predictive machine learning models. However, using large datasets may not be feasible due to computational limi…
physics.chem-ph2023
On the Interplay of Subset Selection and Informed Graph Neural Networks
Niklas Breustedt, Paolo Climaco, Jochen Garcke +5
Machine learning techniques paired with the availability of massive datasets dramatically enhance our ability to explore the chemical compound space by providing fast and accurate…