The bliss of dimensionality: how an unsupervised criterion identifies optimal low-resolution representations of high-dimensional datasets

Documenti analoghi

• Density of states in neural networks: an in-depth exploration of learning in parameter space
  di: Mele, Margherita, et al.
  Pubblicazione: (2024)
• Determining the optimal structural resolution of proteins through an information-theoretic analysis of their conformational ensemble
  di: Mele, Margherita, et al.
  Pubblicazione: (2023)
• EXCOGITO, an extensible coarse-graining toolbox for the investigation of biomolecules by means of low-resolution representation
  di: Giulini, Marco, et al.
  Pubblicazione: (2024)
• Milestoning estimators of dissipation in systems observed at a coarse resolution: When ignorance is truly bliss
  di: Blom, Kristian, et al.
  Pubblicazione: (2023)
• From high-dimensional committors to reactive insights
  di: Strand, Nils E., et al.
  Pubblicazione: (2024)