I have some basic knowledge about deep learning methods (fully connected and convolutional NNs). I would like to expand my knowledge of deep learning which could be beneficial for an operations researcher. What resource/book would you suggest for reading?
This is the book that I used for my class at VT: https://www.deeplearningbook.org/
This is another book that was recommended there: https://d2l.ai/
This book on online learning is also useful: https://www.cs.huji.ac.il/~shais/papers/OLsurvey.pdf "Online Learning and Online Convex Optimization" by Shai Shalev-Shwartz.
Some papers I found helpful from Van Hentenryck: "Fast Approximations for Job Shop Scheduling: A Lagrangian Dual Deep Learning Method", "Predicting AC Optimal Power Flows: Combining Deep Learning and Lagrangian Dual Methods".
Also, this paper is helpful: https://arxiv.org/pdf/1705.03341.pdf "Stable Architectures for Deep Neural Networks"
If you have a graph background: https://web.njit.edu/~ym329/dlg_book/