Search Results for author:
Found 4 papers, 0 papers with code
Universal Feature Selection for Simultaneous Interpretability of Multitask Datasets
Extracting meaningful features from complex, high-dimensional datasets across scientific domains remains challenging.
Antiviral Drug-Membrane Permeability: the Viral Envelope and Cellular Organelles
To shorten the time required to find effective new drugs, like antivirals, a key parameter to consider is membrane permeability, as a compound intended for an intracellular target with poor permeability will have low efficacy.
A New Data-Driven Sparse-Learning Approach to Study Chemical Reaction Networks
In this paper, we introduce a novel approach for the identification of the influential reactions in chemical reaction networks for combustion applications, using a data-driven sparse-learning technique.
A Data-Driven Sparse-Learning Approach to Model Reduction in Chemical Reaction Networks
In this paper, we propose an optimization-based sparse learning approach to identify the set of most influential reactions in a chemical reaction network.
