Probabilistic Decomposed Linear Dynamical Systems for Robust Discovery of Latent Neural Dynamics

Documenti analoghi

• Decomposed Linear Dynamical Systems (dLDS) for learning the latent components of neural dynamics
  di: Mudrik, Noga, et al.
  Pubblicazione: (2022)
• LINOCS: Lookahead Inference of Networked Operators for Continuous Stability
  di: Mudrik, Noga, et al.
  Pubblicazione: (2024)
• LORE: Jointly Learning the Intrinsic Dimensionality and Relative Similarity Structure From Ordinal Data
  di: Anand, Vivek, et al.
  Pubblicazione: (2026)
• Self-Supervised Dynamical System Representations for Physiological Time-Series
  di: Chen, Yenho, et al.
  Pubblicazione: (2025)
• Neighbor Embedding for High-Dimensional Sparse Poisson Data
  di: Mudrik, Noga, et al.
  Pubblicazione: (2026)