40- Deep Learning/ClipID:21107 previous clip next clip

Recording date 2020-10-12

Course

Deep Learning

Language

English

Organisational Unit

Friedrich-Alexander-Universität Erlangen-Nürnberg

Producer

Friedrich-Alexander-Universität Erlangen-Nürnberg

Deep Learning - Visualization & Attention Part 5

This video explains the concepts of attention in deep learning.

For reminders to watch the new video follow on Twitter or LinkedIn.

Video References:
Wall-E und Eve
Wall-E Shopping Cart
Lex Fridman's Channel

Further Reading:
A gentle Introduction to Deep Learning

Links
Yosinski et al.: Deep Visualization Toolbox 

Olah et al.: Feature Visualization 

Adam Harley: MNIST Demo 

Referemces
[1] Dzmitry Bahdanau, Kyunghyun Cho, and Yoshua Bengio. “Neural Machine Translation by Jointly Learning to Align and Translate”. In: 3rd International Conference on Learning Representations, ICLR 2015, San Diego, 2015.
[2] T. B. Brown, D. Mané, A. Roy, et al. “Adversarial Patch”. In: ArXiv e-prints (Dec. 2017). arXiv: 1712.09665 [cs.CV].
[3] Jianpeng Cheng, Li Dong, and Mirella Lapata. “Long Short-Term Memory-Networks for Machine Reading”. In: CoRR abs/1601.06733 (2016). arXiv: 1601.06733.
[4] Jacob Devlin, Ming-Wei Chang, Kenton Lee, et al. “BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding”. In: CoRR abs/1810.04805 (2018). arXiv: 1810.04805.
[5] Neil Frazer. Neural Network Follies. 1998. URL: https://neil.fraser.name/writing/tank/ (visited on 01/07/2018).
[6] Ross B. Girshick, Jeff Donahue, Trevor Darrell, et al. “Rich feature hierarchies for accurate object detection and semantic segmentation”. In: CoRR abs/1311.2524 (2013). arXiv: 1311.2524.
[7] Alex Graves, Greg Wayne, and Ivo Danihelka. “Neural Turing Machines”. In: CoRR abs/1410.5401 (2014). arXiv: 1410.5401.
[8] Karol Gregor, Ivo Danihelka, Alex Graves, et al. “DRAW: A Recurrent Neural Network For Image Generation”. In: Proceedings of the 32nd International Conference on Machine Learning. Vol. 37. Proceedings of Machine Learning Research. Lille, France: PMLR, July 2015, pp. 1462–1471.
[9] Nal Kalchbrenner, Lasse Espeholt, Karen Simonyan, et al. “Neural Machine Translation in Linear Time”. In: CoRR abs/1610.10099 (2016). arXiv: 1610.10099.
[10] L. N. Kanal and N. C. Randall. “Recognition System Design by Statistical Analysis”. In: Proceedings of the 1964 19th ACM National Conference. ACM ’64. New York, NY, USA: ACM, 1964, pp. 42.501–42.5020.
[11] Andrej Karpathy. t-SNE visualization of CNN codes. URL: http://cs.stanford.edu/people/karpathy/cnnembed/ (visited on 01/07/2018).
[12] Alex Krizhevsky, Ilya Sutskever, and Geoffrey E Hinton. “ImageNet Classification with Deep Convolutional Neural Networks”. In: Advances In Neural Information Processing Systems 25. Curran Associates, Inc., 2012, pp. 1097–1105. arXiv: 1102.0183.
[13] Thang Luong, Hieu Pham, and Christopher D. Manning. “Effective Approaches to Attention-based Neural Machine Translation”. In: Proceedings of the 2015 Conference on Empirical Methods in Natural Language Lisbon, Portugal: Association for Computational Linguistics, Sept. 2015, pp. 1412–1421.
[14] A. Mahendran and A. Vedaldi. “Understanding deep image representations by inverting them”. In: 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR). June 2015, pp. 5188–5196.
[15] Andreas Maier, Stefan Wenhardt, Tino Haderlein, et al. “A Microphone-independent Visualization Technique for Speech Disorders”. In: Proceedings of the 10th Annual Conference of the International Speech Communication Brighton, England, 2009, pp. 951–954.
[16] Volodymyr Mnih, Nicolas Heess, Alex Graves, et al. “Recurrent Models of Visual Attention”. In: CoRR abs/1406.6247 (2014). arXiv: 1406.6247.
[17] Chris Olah, Alexander Mordvintsev, and Ludwig Schubert. “Feature Visualization”. In: Distill (2017). https://distill.pub/2017/feature-visualization.
[18] Prajit Ramachandran, Niki Parmar, Ashish Vaswani, et al. “Stand-Alone Self-Attention in Vision Models”. In: arXiv e-prints, arXiv:1906.05909 (June 2019), arXiv:1906.05909. arXiv: 1906.05909 [cs.CV].
[19] Mahmood Sharif, Sruti Bhagavatula, Lujo Bauer, et al. “Accessorize to a Crime: Real and Stealthy Attacks on State-of-the-Art Face Recognition”. In: Proceedings of the 2016 ACM SIGSAC Conference on Computer and Communications CCS ’16. Vienna, Austria: ACM, 2016, pp. 1528–1540. A.
[20] K. Simonyan, A. Vedaldi, and A. Zisserman. “Deep Inside Convolutional Networks: Visualising Image Classification Models and Saliency Maps”. In: International Conference on Learning Representations (ICLR) (workshop track). 2014.
[21] J.T. Springenberg, A. Dosovitskiy, T. Brox, et al. “Striving for Simplicity: The All Convolutional Net”. In: International Conference on Learning Representations (ICRL) (workshop track). 2015.
[22] Dmitry Ulyanov, Andrea Vedaldi, and Victor S. Lempitsky. “Deep Image Prior”. In: CoRR abs/1711.10925 (2017). arXiv: 1711.10925.
[23] Ashish Vaswani, Noam Shazeer, Niki Parmar, et al. “Attention Is All You Need”. In: CoRR abs/1706.03762 (2017). arXiv: 1706.03762.
[24] Kelvin Xu, Jimmy Ba, Ryan Kiros, et al. “Show, Attend and Tell: Neural Image Caption Generation with Visual Attention”. In: CoRR abs/1502.03044 (2015). arXiv: 1502.03044.
[25] Jason Yosinski, Jeff Clune, Anh Mai Nguyen, et al. “Understanding Neural Networks Through Deep Visualization”. In: CoRR abs/1506.06579 (2015). arXiv: 1506.06579.
[26] Matthew D. Zeiler and Rob Fergus. “Visualizing and Understanding Convolutional Networks”. In: Computer Vision – ECCV 2014: 13th European Conference, Zurich, Switzerland, Cham: Springer International Publishing, 2014, pp. 818–833.
[27] Han Zhang, Ian Goodfellow, Dimitris Metaxas, et al. “Self-Attention Generative Adversarial Networks”. In: Proceedings of the 36th International Conference on Machine Learning. Vol. 97. Proceedings of Machine Learning Research. Long Beach, California, USA: PMLR, Sept. 2019, pp. 7354–7363. A.

Up next

Maier, Andreas
Prof. Dr. Andreas Maier
2020-10-12
IdM-login
Maier, Andreas
Prof. Dr. Andreas Maier
2020-10-12
IdM-login
Maier, Andreas
Prof. Dr. Andreas Maier
2020-10-13
IdM-login
Maier, Andreas
Prof. Dr. Andreas Maier
2020-10-12
IdM-login
Maier, Andreas
Prof. Dr. Andreas Maier
2020-10-12
IdM-login

More clips in this category "Friedrich-Alexander-Universität Erlangen-Nürnberg"

2020-04-24
IdM-login
protected  
2020-05-15
Studon
protected