TY - GEN A1 - Kowarik, Stefan A1 - Pithan, L. T1 - kowarik-labs/AI-reflectivity: v0.1 N2 - AI-reflectivity is a code based on artificial neural networks trained with simulated reflectivity data that quickly predicts film parameters from experimental X-ray reflectivity curves. This project has a common root with (ML-reflectivity)[https://github.com/schreiber-lab/ML-reflectivity] and evolved in parallel. Both are linked to the following publication: Fast Fitting of Reflectivity Data of Growing Thin Films Using Neural Networks A. Greco, V. Starostin, C. Karapanagiotis, A. Hinderhofer, A. Gerlach, L. Pithan, S. Liehr, F. Schreiber, S. Kowarik (2019). J. Appl. Cryst. For an online live demonstration using a pre-trained network have a look at github. PB - Zenodo CY - Geneva KW - Artificial neural networks KW - X-ray reflectivity PY - 2019 UR - https://opus4.kobv.de/opus4-bam/frontdoor/index/index/docId/51888 AN - OPUS4-51888 AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany