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[Suggestion] New paper #134

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@ljding94

Title: A machine learning inversion scheme for determining interaction from scattering

Short description: this work use MD simulation to generate scattering data, which then be used for ML inference

Link to paper: https://www.nature.com/articles/s42005-021-00778-y

also some other papers on simulation-based ML inference for scattering:

Title: Small angle scattering of diblock copolymers profiled by machine learning
Link to paper: https://pubs.aip.org/aip/jcp/article/156/13/131101/2840953

Title: Inferring effective electrostatic interaction of charge-stabilized colloids from scattering using deep learning
Link to paper: https://journals.iucr.org/paper?buy=yes&cnor=tu5049&showscheme=yes&sing=yes

Title: Inferring colloidal interaction from scattering by machine learning
Link to paper: https://www-sciencedirect-com.ornl.idm.oclc.org/science/article/pii/S266705692300007X

Title: Machine Learning Inversion from Scattering for Mechanically Driven Polymers
Link to paper: https://arxiv.org/abs/2410.05574

Title: Machine Learning-Assisted Profiling of Ladder Polymer Structure using Scattering
Link to paper: https://arxiv.org/abs/2411.00134

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