There is an interesting wave of papers on possible applications of deep learning and neural networks on the string theory landscape.

Evidently it’s something interesting to work with, mainly if you’re a student looking for a “manageable big problem” to tackle and has interest on computational physics. . . keep an eye on this stuff.

- Deep-Learning the Landscape – Yang-Hui He
- Machine Learning of Calabi-Yau Volumes – Daniel Krefl and Rak-Kyeong Seong
- Evolving neural networks with genetic algorithms to study theString Landscape – Fabian Ruehle