Citation & References#

If you use MaldiDeepKit in academic work, please cite this repository until the companion paper is available:

Citation will be available soon. A companion benchmark paper comparing the four MaldiDeepKit architectures on DRIAMS-derived subsets is in preparation.

Alongside the upstream references for the architectures bundled in the package:

  • ResNet - He K, Zhang X, Ren S, Sun J (2016). Deep Residual Learning for Image Recognition. CVPR. doi:10.1109/CVPR.2016.90

  • Vision Transformer - Dosovitskiy A, Beyer L, Kolesnikov A, et al. (2021). An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale. ICLR. arXiv:2010.11929

  • LayerScale - Touvron H, Cord M, Sablayrolles A, et al. (2021). Going deeper with Image Transformers. ICCV. arXiv:2103.17239

  • Stochastic Depth - Huang G, Sun Y, Liu Z, Sedra D, Weinberger K (2016). Deep Networks with Stochastic Depth. ECCV. arXiv:1603.09382

  • Temperature Scaling - Guo C, Pleiss G, Sun Y, Weinberger KQ (2017). On Calibration of Modern Neural Networks. ICML. arXiv:1706.04599

  • Sharpness-Aware Minimization - Foret P, Kleiner A, Mobahi H, Neyshabur B (2021). Sharpness-Aware Minimization for Efficiently Improving Generalization. ICLR. arXiv:2010.01412

Related publications using the wider MaldiSuite:

  • Rocchi, E., Nicitra, E., Calvo, M. et al. Combining mass spectrometry and machine learning models for predicting Klebsiella pneumoniae antimicrobial resistance: a multicenter experience from clinical isolates in Italy. BMC Microbiol (2026). doi:10.1186/s12866-025-04657-2