Neural network learning and quantum gravity

Artificial intelligence (68Txx) Quantum field theory; related classical field theories (81Txx) Unified, higher-dimensional and super field theories (83Exx)

Cites Work

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Counting flux vacua
Calabi-Yau manifolds and SU(3) structure
Deep learning and k-means clustering in heterotic string vacua with line bundles
Computational complexity of the landscape. I.
On the geometry of the string landscape and the swampland
Computational complexity of the landscape. II: Cosmological considerations
Persistent homology and string vacua
Evolving neural networks with genetic algorithms to study the string landscape
Machine learning in the string landscape
From algebraic geometry to machine learning
Moduli-dependent Calabi-Yau and SU(3)-structure metrics from machine learning
Holomorphic feedforward networks
Deformed WZW models and Hodge theory. I.
Data science applications to string theory
Machine learning Calabi-Yau four-folds
Searching the landscape of flux vacua with genetic algorithms
Branes with brains: exploring string vacua with deep reinforcement learning
Inflation as an information bottleneck: a strategy for identifying universality classes and making robust predictions
Topological data analysis for the string landscape
Estimating Calabi-Yau hypersurface and triangulation counts with equation learners
The F-theory geometry with most flux vacua
A new decision method for elementary algebra
Tameness, strings, and the distance conjecture
Taming the landscape of effective theories
134 billion intersecting brane models
Sets, Models and Proofs
Alfred Tarski's elimination theory for real closed fields
Vapnik-Chervonenkis Classes of Definable Sets
Model Theory
Neural Network Learning
Persistent homology and non-Gaussianity
Tame topology of arithmetic quotients and algebraicity of Hodge loci
Machine Learning Line Bundle Cohomology
Finiteness for self-dual classes in integral variations of Hodge structure
Statistical Predictions in String Theory and Deep Generative Models
Heterotic String Model Building with Monad Bundles and Reinforcement Learning
Cosmic Inflation and Genetic Algorithms
New Calabi-Yau manifolds from genetic algorithms
Decoding nature with nature's tools: heterotic line bundle models of particle physics with genetic algorithms and quantum annealing
Complexity in tame quantum theories

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