Difference between revisions of "User:Lwebster"
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* Received Gaussian Processes Matlab script from [http://www.marquette.edu/mscs/facstaff-spiller.shtml Dr. Elaine Spiller] and wrote down any questions to be clarified | * Received Gaussian Processes Matlab script from [http://www.marquette.edu/mscs/facstaff-spiller.shtml Dr. Elaine Spiller] and wrote down any questions to be clarified | ||
* Attended REU Meeting in which proper presentation techniques were discussed | * Attended REU Meeting in which proper presentation techniques were discussed | ||
| − | * Downloaded a | + | * Downloaded "Assessment of Landslides Susceptibility," a Thesis by Gabriel Legorreta Paulin, to utilize the data and software later |
* Met with [http://www.marquette.edu/mscs/facstaff-spiller.shtml Dr. Elaine Spiller] to clarify project topic and questions. Plans set in place for future work. Weekly goals were reevaluated. | * Met with [http://www.marquette.edu/mscs/facstaff-spiller.shtml Dr. Elaine Spiller] to clarify project topic and questions. Plans set in place for future work. Weekly goals were reevaluated. | ||
* Downloaded Matplotlib in Python to learn graphing in Python | * Downloaded Matplotlib in Python to learn graphing in Python | ||
| Line 58: | Line 58: | ||
* Met with [http://www.marquette.edu/mscs/facstaff-spiller.shtml Dr. Elaine Spiller] to discuss next steps | * Met with [http://www.marquette.edu/mscs/facstaff-spiller.shtml Dr. Elaine Spiller] to discuss next steps | ||
* Began converting paper log and sources into Overleaf | * Began converting paper log and sources into Overleaf | ||
| − | * Began reading new article, Diagnostics for Gaussian Process Emulators | + | * Began reading new article, "Diagnostics for Gaussian Process Emulators" |
=== Week 4 (6/18/18-6/22/18) === | === Week 4 (6/18/18-6/22/18) === | ||
| − | '''Overall Goal:''' Read Gaussian Process Diagnostics paper, read about linear regression (online course notes, my old course notes, and the first 3 chapters of the Landslide Thesis) | + | '''Overall Goal:''' Read Gaussian Process Diagnostics paper, read about linear regression (online course notes, online tutorials, my old course notes, and the first 3 chapters of the Landslide Thesis) |
* Ran into an issue with the Landslide software, so those activities have been put on hold | * Ran into an issue with the Landslide software, so those activities have been put on hold | ||
| − | * Finished reading Diagnostics for Gaussian Process Emulators | + | * Finished reading and taking notes on "Diagnostics for Gaussian Process Emulators" |
| − | * | + | * Read the first 3 chapters of "Assessment of Landslides Susceptibility" |
| + | * Continued reading on linear regression | ||
Revision as of 20:45, 19 June 2018
Contents
Personal Info
Lindsay Webster is a double major in Mathematics and Theatre Arts in the Honors Program at Marquette University. She will graduate in 2019. She is the Production Manager of Marquette's Helfaer Theatre, where she also serves as a performer and occasionally a set designer.
She recently made a probabilistic mathematical model to predict the winner of Best Musical at the annual Tony Awards (and as of June 10th, it officially works!!!). So if you're wondering how Mathematics and Theatre Arts combine, that's it.
Research Topic
Coupling Landslide Hazards
How Gaussian Stochastic Processes can be used to predict landslide behaviors.
Weekly Log
Week 1 (5/29/18-6/1/18)
Overall Goal: Clarify project topic, clear up any confusions on the previous reading, read a different take on Gaussian Stochastic Processes
- Attended REU Orientation
- Met Dr. Elaine Spiller and discussed previously assigned reading from the week before (Chapter 1-2,2 of Gaussian Processes for Machine Learning, C. E. Rasmussen & C. K. I. Williams)
- Set up lab accounts and learned how to access the Wiki page
- Learned about Library resources
- Met with Dr. Elaine Spiller and was assigned new readings regarding Gaussian Stochastic Processes for the next week
- Read about The Random Function (RF) Model (Jerome Sacks and William J. Welch)
- Read about the Random Function Parameter Estimation, Prediction Uncertainty, and Diagnostics (Jerome Sacks and William J. Welch)
- Read about Gaussian Stochastic Processes Designs (Jerome Sacks and William J. Welch)
- Read about Uses of Random Function Models (Jerome Sacks and William J. Welch)
- Read about Choosing a Random Function Model (Jerome Sacks and William J. Welch)
Week 2 (6/4/18-6/8/18)
Overall Goal: Explore Gaussian Matlab script in 1d and 2d, re-examine accomplishments and challenges and update weekly goals as needed, begin research paper
- Reviewed all readings from last week
- Began Responsible Conduct of Research Training - all 3 Modules completed
- Watched educational videos on GaSP and took notes
- Began research paper - created a journal-style format to write in as project develops
- Received Gaussian Processes Matlab script from Dr. Elaine Spiller and wrote down any questions to be clarified
- Attended REU Meeting in which proper presentation techniques were discussed
- Downloaded "Assessment of Landslides Susceptibility," a Thesis by Gabriel Legorreta Paulin, to utilize the data and software later
- Met with Dr. Elaine Spiller to clarify project topic and questions. Plans set in place for future work. Weekly goals were reevaluated.
- Downloaded Matplotlib in Python to learn graphing in Python
- Began learning graphing and matrices in Python
Week 3 (6/11/18-6/15/18)
Overall Goal: Translate Matlab script to Python, explore the effects of different values of theta, find inbuilt function to optimize the parameters of the Python Gaussian Model
- Learned basic Matrix operations in Python - vectors, matrices, multiplying, dividing, dot products, inverses, transposes
- Learned basic graphs in Python - line plot, bar graph, histogram, scatter plot, stack plot, pie chart
- SKLearn was downloaded into Python to utilize the inbuilt GaSP functions
- Utilized online tutorials to create a test prior and posterior GaSP model (Created by Jan Hendrik Metzen)
- Altered test model to be prepared to receive and operate on mudslide data
- Created a Python function to output the predicted y value when prompted with a specific x value, based on the GaSP model
- Updated Paper Log and sources
- Attend Responsible Conduct of Research face-to-face training
- Downloaded LaTeX to prepare writing final research paper (may use Overleaf instead)
- Observed the effects of a changing theta (the higher the theta, the smaller correlation between predicted lines)
- Optimized the parameters of the Python Gaussian Model and created python functions to output those optimized values
- Met with Dr. Elaine Spiller to discuss next steps
- Began converting paper log and sources into Overleaf
- Began reading new article, "Diagnostics for Gaussian Process Emulators"
Week 4 (6/18/18-6/22/18)
Overall Goal: Read Gaussian Process Diagnostics paper, read about linear regression (online course notes, online tutorials, my old course notes, and the first 3 chapters of the Landslide Thesis)
- Ran into an issue with the Landslide software, so those activities have been put on hold
- Finished reading and taking notes on "Diagnostics for Gaussian Process Emulators"
- Read the first 3 chapters of "Assessment of Landslides Susceptibility"
- Continued reading on linear regression
Week 5 (6/25/18-6/29/18)
Overall Goal: Make progress in fitting the Gaussian processes to landslide simulations, prepare practice presentation
Week 6 (7/2/18-7/6/18)
Overall Goal: Fit the Gaussian processes to landslide simulations, begin project poster
Week 7 (7/9/18-7/13/18)
Overall Goal: Begin coupling the two models
Week 8 (7/16/18-7/20/18)
Overall Goal: Continue coupling the two models, finish project poster
Week 9 (7/23/18-7/27/18)
Overall Goal: Finish coupling the models, finish research paper
Week 10 (7/30/18-8/3/18)
Overall Goal: Prepare for final presentation
