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2. Data from "Homogeneous ice nucleation in an ab initio machine learning model"
3. Data from "Signatures of a liquid-liquid transition in an ab initio deep neural network model for water"
4. Deep convolutional neural networks for multi-scale time-series classification and application to disruption prediction in fusion devices
5. Fluorescence Reconstruction Microscopy Data: Keratinocyte (10x) Phase to Nuclei (DAPI)
6. Fluorescence Reconstruction Microscopy Data: MDCK (20x) DIC to Nuclei (DAPI) and E-Cadherin (RFP)
7. Fluorescence Reconstruction Microscopy: Complete Testing Dataset
8. MLP neural network trained on the QCL [-5, +20] Å dataset
9. Machine Learning Characterization of Alfvénic and Sub-Alfvénic Chirping and Correlation With Fast-Ion Loss at NSTX
10. Machine Learning Characterization of Alfvénic and Sub-Alfvénic Chirping and Correlation With Fast-Ion Loss at NSTX
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