Gradient-based meta-learning over neural state-space models adapts a model to a new dynamical system with little target data and few gradient steps, with physical constraints embedded in the architecture.
State-space neural network. Properties and application,
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.LG 1years
2025 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
Meta-Learning for Physically-Constrained Neural System Identification
Gradient-based meta-learning over neural state-space models adapts a model to a new dynamical system with little target data and few gradient steps, with physical constraints embedded in the architecture.