User:Skohli

Personal Information

• Incoming junior | Computer science major at Marquette

• Working with Dr. Povinelli in the GasDay Lab

Weekly Log

Week 1 (May 30 - June 2)

• Discussed preliminary project ideas with other researchers and mentor.
• Attended library tour.
• Attended the talk on how to conduct research.
• Read paper on the GEFcomp2014- Hongetal2016
• Read Bengio Learning Deep Architectures for AI
• Found more material to read.
• Attended weekly book club meeting as suggested by mentor
• Read chapter 1-3 in the book titled Deep Learning Book
• Read Probabilistic Forecasting by Gneting and Katzfuss
• Additive models and robust aggregation for GEFcomp2014 probabilistic electric load and electricity price forecasting by Gaillard, Goude, Nedellec.
• Read DeepAR: Probabilistic Forecasting with Autoregressive Recurrent Networks
• Met Dr. Povinelli 4 times: to discuss possible project topics, to get oriented with the lab, to decide on a project topic, and to establish weekly milestones

Week 2 (June 5 - June 9)

• Read chapter 4 of deep neural network book
• Attended GasDay camp
  • Learned what GasDay does
  • Benefits of working at GasDay
  • Further research opportunities at GasDay
  • How to work in a team
• Attended the Ethical research training
  • Learned key concepts such as not fabricating, falsifying, and plagiarizing
• Read
  • 10.1109/PMAPS.2016.7764155
  • https://doi.org/10.1016/j.energy.2016.07.090
  • http://www.sciencedirect.com/science/article/pii/S1568494617302946
• Met Dr. Povinelli 3 times to discuss current progress
• Attended weekly book club meeting as suggested by mentor

Week 3 (June 12 - June 16)

• Tasks undertaken to improve skills
  • Completed 6 weeks of the coursera tutorial on Machine Learning
  • Completed 6 weeks of the Stanford class on Convolution Neural Networks for Visual Recognition
  • Learned basics of Python
• Completed portion of online RCR training
• Attended weekly book club meeting as suggested by mentor
• Met Dr. Povinelli 2 times to discuss current progress
• Collected data

Week 4 (June 19 - June 23)

• Go through Machine Learning tutorials online
• Try to learn tensorflow
• Try to learn Quantile regression
• Understand Pinball Loss Function

Week 5(June 26 - June 30)

• Prepare slides for presentation
• Present presentation
• Work with Keras
• Make prelimary models
• Wish for faster computers
• Implement the pinball loss function with different methods:
  • Convolutional neural networks
  • ResNets
  • Feed Forward
    • Keras api for models
    • WIthout Keras api for models
• Implement the Winkler Score
• Read Attention is all you need

Week 6 (July 3 - July 6)

• https://arxiv.org/pdf/1706.02515.pdf
• Tried different deep learning techniques
  • CNN
  • ResNet
  • RNNS
  • Feed forward
    • Hyperamaters
• Presented at GasDay
• Attended how to make a good poster presentation

Week 7 (July 8 - July 15)

• Adapted the technique from DeepAR
• Tried different methods surrounding it
• Choose which method I will stick with

Week 8(July 17- July 21)

• Spent week trying to see why val and test scores are extremely different
• Ran models with different data sets to see why that is happening

Week 9(July 24 - July 28)

• Finishing up poster
• Finishing up presentation
• Starting to write paper
• Cleaning code