Data Driven Modeling
On this Page, you will find examples of some of my favorite work done for ENM 360 throughout the fall of 2020. Most images and links are from completed HW assignments throughout the semester. I would like to give a huge thank you to Dr. Perdikaris and George Kissas for their support throughout the semester and an amazing class. The original code can be found by following the links on the buttons.
Bayesian Linear Regression: MAP and MLE estimates along with samples from the predictive posterior distributions for different basis features (M = 8).
Lagrange Interpolation: Runge’s Phenomenon, Chebyshev-Gauss-Lobatto, and Chebyshev-Gauss points. (Also includes implementations of various numerical integration and differentiation schemes).
