This post explores machine learning models for classifying policy area of congressional bills.

Explore the pivotal role of Coulomb matrices in representing molecular structures for machine learning. Learn about their calculation and application as a molecular descriptor in advancing computational chemistry.

This study provides a detailed exploration of the legislative processes, party dynamics, and key activities of the 117th Congress, employing data visualization and NLP techniques.

The Kabsch algorithm is an algorithm for computing the optimal rigid body transformation for aligning two sets of paired points. This post covers its implementation in NumPy, PyTorch, TensorFlow, and JAX.

This post explores the simulation of Pt adatom diffusion on a Pt(100) surface using LAMMPS, suggesting its potential as a simple toy model for machine learning applications, updating the previous Cu adatom diffusion simulation.