Applying Topological Uncertainty to hidden-layer activations of a trained FNN detects failed neutron-star EoS inferences with over 90% success in the best-tested configuration.
Topological data analysis and machine learning
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abstract
Topological data analysis refers to approaches for systematically and reliably computing abstract ``shapes'' of complex data sets. There are various applications of topological data analysis in life and data sciences, with growing interest among physicists. We present a concise yet (we hope) comprehensive review of applications of topological data analysis to physics and machine learning problems in physics including the detection of phase transitions. We finish with a preview of anticipated directions for future research.
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Topological Uncertainty for Anomaly Detection in the Neural-network EoS Inference with Neutron Star Data
Applying Topological Uncertainty to hidden-layer activations of a trained FNN detects failed neutron-star EoS inferences with over 90% success in the best-tested configuration.