# Lecture - Theories of Deep Learning MT25, II, Why deep learning

> Source: https://ollybritton.com/notes/uni/part-c/mt25/theories-of-deep-learning/lectures/ii/ · Updated: 2025-10-19 · Tags: uni, lecture

- [Course - Theories of Deep Learning MT25](https://ollybritton.com/notes/uni/part-c/mt25/theories-of-deep-learning/)

### Papers mentioned
- [ImageNet Large Scale Visual Recognition Challenge](https://link.springer.com/article/10.1007/s11263-015-0816-y)
- [ImageNet Classification with Deep Convolutional Neural Networks, Krizhevsky](https://papers.nips.cc/paper_files/paper/2012/file/c399862d3b9d6b76c8436e924a68c45b-Paper.pdf)
- [Paper - Mastering the Game of Go with Deep Neural Networks and Tree Search](https://ollybritton.com/notes/papers/mastering-the-game-of-go/)
- [Image Style Transfer Using Convolutional Neural Networks, Gatys](https://www.cv-foundation.org/openaccess/content_cvpr_2016/papers/Gatys_Image_Style_Transfer_CVPR_2016_paper.pdf)
- [Visually Indicated Sounds, Owens](https://arxiv.org/pdf/1512.08512)
- [Zero-Shot Text-to-Image Generation](https://arxiv.org/abs/2102.12092)
- [CMU DeepLens: deep learning for automatic image-based galaxy–galaxy strong lens finding](https://academic.oup.com/mnras/article/473/3/3895/3930852)
- [Highly accurate protein structure prediction with AlphaFold](https://www.nature.com/articles/s41586-021-03819-2)
- [Skilful precipitation nowcasting using deep generative models of radar](https://www.nature.com/articles/s41586-021-03854-z)
- [Advancing mathematics by guiding human intuition with AI](https://www.nature.com/articles/s41586-021-04086-x)
- [A Deep Learning Approach to Antibiotic Discovery](https://www.cell.com/cell/fulltext/S0092-8674(20)30102-1?_returnURL=https%3A%2F%2Flinkinghub.elsevier.com%2Fretrieve%2Fpii%2FS0092867420301021%3Fshowall%3Dtrue)
- [Article - Deep, deep trouble, Elad](https://ollybritton.com/notes/uni/part-c/mt25/theories-of-deep-learning/reading/article-deep-deep-trouble-elad/)
- [Paper - Representation Benefits of Deep Feedforward Networks, Telgarsky (2015)](https://ollybritton.com/notes/uni/part-c/mt25/theories-of-deep-learning/reading/paper-representation-benefits-of-deep-feedforward-networks-telgarsky-2015/)

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