Statistical Sensitivity Analysis:
-I will send you a paper on the topic. You will need to read and implement the method. This would require you to get comfortable with statistics. Once you understand the method, coding it down is very easy. “Attached below”
Requirements: Please type down the report in Word
1) Abstract (<200 words)
2) Background in layman language (i.e., no jargons and no excessive use of field-specific abbreviations). Write about the importance and applications of the topic you are investigating, what has been done in the literature, and how your project improves/related to the prior works and this class.<2 pages.
3) Technical details. <3 pages.
4) Results. <3 pages
5) conclusion. Summarize the report. Also, write about what you learned in this project. 1 page.
6) Appendix. Codes, detailed formulas/discussions/results
Rubric:
The most important criterion is “implementing/developing a method/algorithm that is relevant to one of the topics we have discussed in the class”. You should discuss your results and show that you have understood the topic. Please write your report in a professional style (i.e., avoid using slangs, …).
Topics Discussed in Class:
-Optimization (Gradient-based optimization, Heuristic Optimization, Multi-Objective Optimization)
-Gaussian Processes (GP modeling)
-Bayesian Calibration
Sample Solution
