1 citations · 1 across the 2 of their papers we have counts for
2 papers
stat.ML2024
A Pipeline for Data-Driven Learning of Topological Features with Applications to Protein Stability Prediction
Amish Mishra, Francis Motta
In this paper, we propose a data-driven method to learn interpretable topological features of biomolecular data and demonstrate the efficacy of parsimonious models trained on topol…
stat.CO2023★ 1 cited
Stability and Machine Learning Applications of Persistent Homology Using the Delaunay-Rips Complex
Amish Mishra, Francis C. Motta
In this paper we define, implement, and investigate a simplicial complex construction for computing persistent homology of Euclidean point cloud data, which we call the Delaunay-Ri…