Here you’ll find selected works at the intersection of applied mathematics, machine learning, philosophy, and computational modeling.
- Modified Gram-Schmidt (MGS): A double orthogonalization implementation yielding near-perfect reconstruction and numerical stability.
- Convex Optimization & Duality: Applications of probabilistic and deterministic gradient descent in optimization theory.
- Phenomenology & Mathematics: Essays exploring mathematical structure, general ontology, and the metaphysics of modeling.