Search Results for author:
Found 4 papers, 3 papers with code
Neural parameter calibration and uncertainty quantification for epidemic forecasting
The recent COVID-19 pandemic has thrown the importance of accurately forecasting contagion dynamics and learning infection parameters into sharp focus.
GraphKKE: Graph Kernel Koopman Embedding for Human Microbiome Analysis
We demonstrate that our method can capture temporary changes in the time-evolving graph on both created synthetic data and real-world data.
Learning chemical reaction networks from trajectory data
We develop a data-driven method to learn chemical reaction networks from trajectory data.
Optimization and Control 92C42, 62M86
Sparse Proteomics Analysis - A compressed sensing-based approach for feature selection and classification of high-dimensional proteomics mass spectrometry data
Results: We present a new algorithm, Sparse Proteomics Analysis (SPA), based on the theory of compressed sensing that allows us to identify a minimal discriminating set of features from mass spectrometry data-sets.
