Science Advances

Supplementary Materials

This PDF file includes:

  • Section S1. Radon transform–based detection method
  • Section S2. In silico generation of flat-folding data
  • Section S3. Prediction on 16 sheets
  • Section S4. Probing the network: Ongoing work
  • Section S5. Another approach to error quantification
  • Section S6. Perturbing the in silico data
  • Fig. S1. In silico–generated flat-folded crease networks.
  • Fig. S2. Comparison between the preprocessed curvature map and the linearized version.
  • Fig. S3. Prediction on a sheet that was crumpled 16 times.
  • Fig. S4. Additional test results.
  • Fig. S5. Prediction accuracy.
  • Fig. S6. Examples of perturbed in silico data.
  • Reference (39)

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