1. Project 7: Modeling Social Network Structures and their Dynamic Evolutions with User- Generated Data from IoT REU Student: Emma Ambrosini Graduate mentors: Marzieh Edraki Faculty Mentor(s): Dr. Guo-Jun Qi
Week 3 (June 5 – June 9, 2017)
Accomplishments:
Got DC-GAN (Deep Convolutional Generative Adversarial Network) code running in tensorflow, edited slightly to show the flow of code
Readied a second DC-GAN code made for torch/lua
Began reading through lua code to better understand it
Introducing myself to torch + lua
Issues/problems encountered and solutions (if any):
Tensorflow slim – not installed on jay
Solved by commenting out lines in code that reference it
Went to tech support, but ran into more issues w/ GPU
Batch normalization contribute wasn’t running
Couldn’t progress past that point, code couldn’t form generator and begin the training proccess
Solved by commenting out references to bn in the layer variables (h0, h1, h2)
Code ran, but end results weren’t very good because of this
Some certain image sets code requires to run were hosted on Dropbox which limits daily downloads
NSF REU Research Experience on Internet of Things 2017

2. Project 7: Modeling Social Network Structures and their Dynamic Evolutions with User- Generated Data from IoT REU Student: Emma Ambrosini Graduate mentors: Marzieh Edraki Faculty Mentor(s): Dr. Guo-Jun Qi
Week 3 (June 5 – June 9, 2017)
Plans for next week:
Run DC-GAN code in Torch, continue understanding flow of code
If slim can be installed, try to get tensorflow code to run properly
Find/read more research papers on both lua & machine learning in general to continue to broaden my perspective on it
Find code for another DC-GAN (tf/python) and get familiar with it
Results of MNIST dataset run through modified tensorflow code
NSF REU Research Experience on Internet of Things 2017