Learning Generalizable Reconstruction of High-Dimensional Neural Dynamics

arXiv:2608.16569 · cs.LG · Submitted 2026-08-17 · Read on arXiv

cs.LG

Submitted: 2026-08-17

Updated: 2026-09-11

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Generalization — 45× in this paper · explained in 13 episodes
• Zero-Shot Generalization — 20× in this paper · explained in 5 episodes
• Fine-Tuning — 19× in this paper · explained in 5 episodes
• Latent Space — 13× in this paper · explained in 7 episodes
• External Validation — 11× in this paper · explained in 2 episodes
• Fidelity — 11× in this paper · explained in 2 episodes
• Latent Dynamics — 10× in this paper · explained in 2 episodes
• Latent Representation — 8× in this paper · explained in 2 episodes
• Aggregation — 7× in this paper · explained in 1 episode
• Robustness — 6× in this paper · explained in 5 episodes
• Latent Representations — 5× in this paper · explained in 3 episodes
• Sparsity — 5× in this paper · explained in 4 episodes
• Accuracy — 4× in this paper · explained in 1 episode
• Adaptation — 4× in this paper · explained in 1 episode
• Interpretability — 4× in this paper · explained in 15 episodes
• Regularization — 3× in this paper · explained in 3 episodes
• Consistency — 2× in this paper · explained in 3 episodes
• Distribution Shift — 2× in this paper · explained in 5 episodes
• Dynamic Mode Decomposition (DMD) — 2× in this paper · explained in 3 episodes
• Embeddings — 2× in this paper · explained in 2 episodes
• Principal Component Analysis (PCA) — 2× in this paper · explained in 4 episodes
• Reconstruction Error — 2× in this paper · explained in 2 episodes
• Zero-Shot Transfer — 2× in this paper · explained in 3 episodes
• Adam — 1× in this paper · explained in 2 episodes
• Alignment — 1× in this paper · explained in 1 episode
• Benchmark — 1× in this paper · explained in 2 episodes
• Chaotic Dynamics — 1× in this paper · explained in 2 episodes
• Computational Biology — 1× in this paper · explained in 2 episodes
• Conventional Dynamic Mode Decomposition — 1× in this paper
• Domain Adaptation — 1× in this paper · explained in 5 episodes
• Feature Extraction — 1× in this paper · explained in 2 episodes
• Generative Model — 1× in this paper · explained in 2 episodes
• Hilbert Space — 1× in this paper · explained in 2 episodes
• Temporal consistency — 1× in this paper · explained in 2 episodes
• Uncertainty Quantification — 1× in this paper · explained in 8 episodes
• Unified Framework — 1× in this paper · explained in 5 episodes

Sources

• A scalable generative model for dynamical system reconstruction from neuroimaging data
• Adversarial Domain Adaptation for Stable Brain-Machine Interfaces
• Zero-Shot Neural Priors for Generalizable Cross-Subject and Cross-Task EEG Decoding
• LFADS - Latent Factor Analysis via Dynamical Systems

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