April 16, 2026 conference-paper Developing an Unsupervised ML Neural Network Autoencoder System to Detect Anomaly in Daily Proton Flux From AMS-02 Experiment DOI: 10.1109/qpain69676.2026.11545735 OpenAlex Authors 0 Author list not loaded yet. Cited by 0 stored of 0 References 2 Search Sort Most cited Newest Oldest Patent citations Title Any typearticle review book-chapter conference-paper preprint dissertation book dataset other Any fieldAgricultural and Biological Sciences Arts and Humanities Biochemistry, Genetics and Molecular Biology Business, Management and Accounting Chemical Engineering Chemistry Computer Science Decision Sciences Dentistry Earth and Planetary Sciences Economics, Econometrics and Finance Energy Engineering Environmental Science Health Professions Immunology and Microbiology Materials Science Mathematics Medicine Neuroscience Nursing Pharmacology, Toxicology and Pharmaceutics Physics and Astronomy Psychology Social Sciences Veterinary Open access Autoencoders for unsupervised anomaly detection in high energy physics 2021 Journal of High Energy Physics article Physics and Astronomy Particle physics theoretical and experimental studies Open access 100 citations Periodicities in the Daily Proton Fluxes from 2011 to 2019 Measured by the Alpha Magnetic Spectrometer on the International Space Station from 1 to 100 GV 2021 Physical Review Letters article Physics and Astronomy Astrophysics and Cosmic Phenomena Open access 95 citations 2 results