Slides from Lectures: CSCE 970

CSCE 970 lecture slides

Lectures 0 and 1: Administrivia and Introduction, Jan 9.
Lecture 2: Artificial Neural Networks and Deep Learning, Jan 11–20, Chapter 4 (1up, 6up)
Also see:
- Deep Visual-Semantic Alignments for Generating Image Descriptions
- Watch this AI drone teach itself how to fly through trial and error
Lecture 3: Regularization and Error Analysis, Jan 23–Feb 6, Chapter 7 (1up, 6up)
Lecture 4: Convolutional Neural Networks, Feb 6–10, Chapter 9 (1up, 6up)
Also see:
Lecture 5: Optimization for Training Deep Models, Feb 13–17, Chapter 8
Also see:
- An overview of gradient descent optimization algorithms by Sebastian Ruder
- Visualizing Optimization Algorithms
Lecture 6: Sequence Modeling: Recurrent and Recursive Nets, Feb 20–24, Chapter 10
Also see:
- Supervised Sequence Labelling with Recurrent Neural Networks by A. Graves, 2012
- Recurrent Neural Networks Tutorial
- Understanding LSTM Networks
- The Unreasonable Effectiveness of Recurrent Neural Networks
- Neural Turing Machines
Lecture 7: Applications, Feb 27–March 8, Chapter 12

8 Inspirational Applications of Deep Learning by Jason Brownlee, 2016
Deep fragment embeddings for bideirectional image sentence mapping by Karpahty et al., NIPS 2014
Rich feature hierarchies for accurate object detection and semantic segmentation by Girshick et al., 2014
ImageNet Classification with Deep Convolutional Neural Networks by Krizhevsky et al., NIPS 2012

Lecture 8: Structured Prediction, March 10–27, Chapters 16–20 (1up, 6up)

Learning with Structured Inputs and Outputs by Christoph Lampert
Structured Learning and Prediction in Computer Vision by Sebastian Nowozin and Christoph H. Lampert
CVPR 2011 Tutorial on Structured Prediction and Learning in Computer Vision
DeepLab: Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution, and Fully Connected CRFs by Chen et al., 2016
A Neural Algorithm of Artistic Style by Gatys et al., 2015.

DeepArt

Lecture 9: Autoencoding, March 29–April 3, Chapters 14–15

Kingma and Welling. Autoencoding Variational Bayes, 2014
Doersch. Tutorial on Variational Autoencoders, 2016

Lecture 10: How to Give a Good Research Talk (1up, 6up)

Tips on presenting technical material

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