Open-source DSL & compiler for classical mechanics — symbolic → numeric → visualization

Lagrangian and Hamiltonian Neural Ordinary Differential Equations (NODEs)

Built on peer-reviewed research accepted at IEEE DSA 2025: "Hamiltonian Neural Networks for Robust Out-of-Time Credit Scoring: Empirical Validation and Temporal Stability Analysis"

Geometric invariant probes that certify quasi-symplectic structure in neural network training. Reveals that BatchNorm breaks the underlying geometry while GroupNorm preserves it.

A collection of original supplementary articles on various Physics and Math topics (WiP)

psipy is a Python library for advanced computational physics and symbolic mathematics. It bridges symbolic representation with numerical simulation, focusing on pseudo-differential operators and spectral methods.