Plans for the week of March 18-22
Dear all, we hope you all had an enjoyable weekend. And welcome back to FYS5429. This is our last session before the Easter break. From April 2 and till the end of the semester our focus will be on generative models only.
The plans for this week are
- Finalize our discussion on Autoencoders (AEs) and Principal Component Analysis (PCA)
- Implement Autoencoders with TensorFlow/Keras and PyTorch
- Start discussion of generative models and possible paths for project 2 if we get time
The Reading recommendations are
- Goodfellow et al chapter 14 on AEs and chapter 16 for start generative models
- Rashcka et al. Their chapter 17 contains a brief introduction only.
In addition you may find the following links of of interest
- Deep Learning Tutorial on AEs from Stanford University http://ufldl.stanford.edu/tutorial/unsupervised/Autoencoders/
- Building AEs in Keras https://blog.keras.io/building-autoencoders-in-keras.html
- Introduction to AEs in TensorFlow https://www.tensorflow.org/tutorials/generative/autoencoder
- Grosse, University of Toronto, Lecture on AEs http://www.cs.toronto.edu/~rgrosse/courses/csc321_2017/slides/lec20.pdf
- Bank et al on AEs see https://arxiv.org/abs/2003.05991
- Baldi and Hornik, Neural networks and principal component analysis: Learning from examples without local minima, Neural Networks 2, 53 (1989)
The lecture material for this week as a jupyter-notebook is at https://github.com/CompPhysics/AdvancedMachineLearning/blob/main/doc/pub/week10/ipynb/week10.ipynb
Else, concerning the coming project deadline for project 1. If you have opted for a longer project, that is merging project 1 and project 2 into one project only, we want you to upload a short (1-2 pages at most) of what you have done and what your plans are for the rest of the semester by the deadline March 22 at midnight. The deadline for project 2 or the final project is June 1 at midnight.
Best wishes to you all,
Keran, Morten and Ruben