Prediction of fatigue–crack growth with neural network-based increment learning scheme

A high-bias, low-variance introduction to Machine Learning for physicists

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Fast evaluation of crack growth path using time series forecasting

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Predicting the 3D fatigue crack growth rate of small cracks using multimodal data via Bayesian networks: In-situ experiments and crystal plasticity simulations

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Machine learning & artificial intelligence in the quantum domain: a review of recent progress

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Prediction of the Diagrams of Fatigue Fracture of D16T Aluminum Alloy by the Methods of Machine Learning

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Learning phase transitions by confusion

(2017) Evert P. L. van Nieuwenburg et al.   Nature Physics

Machine learning phases of matter

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Neural Decoder for Topological Codes

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Solving the quantum many-body problem with artificial neural networks

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An Artificial Neural Network-Based Algorithm for Evaluation of Fatigue Crack Propagation Considering Nonlinear Damage Accumulation

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Deep learning

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The use of artificial neural network (ANN) for modeling the useful life of the failure assessment in blades of steam turbines

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Fatigue crack growth estimation by relevance vector machine

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Prediction of mode-I overload-induced fatigue crack growth rates using neuro-fuzzy approach

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