Schedule

Suggested Readings:

• Perceptron convergence proof

Suggested Readings:

• 5min-Tensor-basics

Suggested Readings:

• Simple CNN training

Suggested Readings:

• Analysis of DNN models for practical applications
• Aggregated Residual Transformations for Deep Neural Networks
• Trimps-Soushen-1, Shao et al. ILSVRC 2016
• Trimps-Soushen-2, Shao et al. ILSVRC 2016
• Squeeze-and-Excitation Networks
• Densely Connected Convolutional Networks
• MobileNets
• ShuffleNets
• NAS

Suggested Readings:

• Xavier Initialization
• Fixup Initialization: Residual learning without Normalization
• Dropout by Srivastave et al.

Suggested Readings:

• Optimization update rules by Sebastian Ruder
• SGD with Momentum, I Sutskever et al. ICML 2013
• Ada Grad, Duchi et al. JMLR, 2011
• Adam, Kingma et al. ICLR 2015
• Some insgihts about lr in dl
• Random search for hyper-parameter selection, Bergstra, JMLR 2012

Suggested Readings:

• LSTM Hochreiter et al. 1997
• Sequence to sequence learning by Sutskever et al. 2014
• Neural Machine Translation with aligning by Bahdanau et al. ICLR 2015

Suggested Readings:

• Sequence to sequence learning by Sutskever et al. NeurIPS 2014
• Neural Machine Translation with aligning by Bahdanau et al. ICLR 2015
• Show Attend and Tell by Xu et al. 2015

Suggested Readings:

• Rich Feature Hierarchies by Girshick et al. CVPR 2014
• Visualizing and Understanding CNNs by Zeiler and Fergus ECCV 2014
• Deep Inside CNNs by Simonyan et al. ICLRW 2014
• Class Activation Maps (CAM) by B Zhou et al. CVPR 2016
• Grad-CAM by Selvaraju et al. NIPSW 2016, ICCV 2017
• CNN-Fixations by Mopuri et al. TIP 2018
• Texture Synthesis using CNNs by Gatys et al. NeurIPS 2015
• DeepDream
• Neural style transfer by Gatys et al. CVPR 2016
• Understanding Deep Representations by Inverting them by A Mahendran et al. CVPR 2015
• Inverting Visual Representations with CNNs by A Dosovitskiy et al. CVPR 2016-

Suggested Readings:

• R-CNN by Girshick et al. CVPR 2014
• Fast R-CNN by Girshick ICCV 2015
• Faster R-CNN by Ren et al. NeurIPS 2015
• SSD by Liu et al. ECCV 2016
• YOLO by Redmon et al. CVPR 2016
• Comparison of CNN object detectors by Huang et al. CVPR 2017
• CornerNet by Law et al. ECCV 2018

Suggested Readings:

• FCN by Long et al. CVPR 2015
• Deconvolution for semantic segmentation by Noh et al. ICCV 2015
• Transposed Convolutions

Suggested Readings:

Suggested Readings:

• Pixel RNN, Google DeepMind, ICML 2016
• Pixel CNN, Google DeepMind, NeurIPS 2016

Suggested Readings:

• Auto-Encoding Variational Bayes, ICLR 2014
• Blogpost on VAE

Suggested Readings:

• GANs, Goodfellow et al, NIPS 2014
• GAN Zoo

Suggested Readings:

• Brief history of CV by Rostyslav Demush