MLPS @ NeurIPS2025

Outline

• Base research from IPAC 2025 paper
  • Remove section on eddy current compensation (but keep it as motivation for going full time series)
  • Elaborate transfer learning techniques for other magnet familes
  • Discuss other available covariates like voltage.
  • Model comparison on fixed dataset, discussion on attention.
  • Show usefulness on removing precycle as we will demonstrate in Dedicated MD 2025-08-13.

Machine learning techniques for hysteresis modeling

• Implemented new models EncoderDecoderLSTM, AttentionLSTM and TransformerLSTM to compare to Temporal Fusion Transformer using validation set on v9.1 with data on flattened MD1.
  • Discuss method comparison with Neural ODEs and Neural Operators.
• Discussion on whether we learn hysteresis or data