Unsupervised machine learning of topological phase transitions from experimental data.
Niklas KämingAnna DawidKorbinian KottmannMaciej LewensteinKlaus SengstockAlexandre DauphinChristof WeitenbergPublished in: Mach. Learn. Sci. Technol. (2021)
Keyphrases
- experimental data
- phase transition
- machine learning
- random constraint satisfaction problems
- supervised learning
- satisfiability problem
- constraint satisfaction
- unsupervised learning
- dynamic model
- hard problems
- randomly generated
- np complete
- combinatorial problems
- graph coloring
- random instances
- learning algorithm
- cellular automata
- sat problem
- mathematical models
- random graphs
- semi supervised
- np complete problems
- data mining
- reinforcement learning
- parameter estimates
- knowledge discovery