Deep Learning Reading Group
This page displays information about the Deep Learning Reading Group at the Mathematics Department at Imperial College London in 2023. The group will aim to learn the fundamentals of the topic (as opposed to recent advances). The main focus is the textbook ‘‘Deep Learning’’ by Goodfellow, Bengio and Courville (2016), but we also read some papers. Meetings are irregularly spaced, but occur on Tuesdays at 4pm in SHER-04-402. If you are an Imperial College London student or staff member and would like to attend, please feel free!
Date | Presenter | To Read | Authors |
---|---|---|---|
23 May | Hector McKimm | Deep Learning (2016), Sections 6.1 - 6.3 | Goodfellow, Bengio and Courville |
30 May | Hector McKimm | Deep Learning (2016), Sections 6.4 - 6.5 | Goodfellow, Bengio and Courville |
6 June | Alice Malivert | Deep Learning (2016), Sections 7.1 - 7.7 | Goodfellow, Bengio and Courville |
20 June | Francesco Vigano | Deep Learning (2016), Sections 7.8 - 7.12 | Goodfellow, Bengio and Courville |
4 July | Arne Wolf | Deep Learning (2016), Sections 8.1 - 8.2 | Goodfellow, Bengio and Courville |
18 July | Yuyang Huang | Deep Learning (2016), Sections 8.3 - 8.5 | Goodfellow, Bengio and Courville |
5 September | Daniel Salnikov | Deep Learning (2016), Sections 9.1 - 9.3 | Goodfellow, Bengio and Courville |
19 September | Toby Severs | Deep Learning (2016), Sections 9.4 - 9.7 | Goodfellow, Bengio and Courville |
26 September | Qinshu Lyu | ImageNet Classification with Deep Convolutional Neural Networks (2012) | Krizhevsky, Sutskever and Hinton |
10 October | Tobias Schroeder | Auto-Encoding Variational Bayes (2014) | Kingma and Welling |