HADES-NN estimates parameters of non-autonomous ODEs with discontinuous forcing by iterating between neural-network smoothing of the input and Levenberg-Marquardt parameter fitting, recovering true parameters where standard methods fail.
A simpler model of the human circadian pacemaker
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
citation-role summary
method 1
citation-polarity summary
fields
cs.LG 1years
2025 1verdicts
CONDITIONAL 1roles
method 1polarities
use method 1representative citing papers
citing papers explorer
-
Neural Network-Based Parameter Estimation for Non-Autonomous Differential Equations with Discontinuous Signals
HADES-NN estimates parameters of non-autonomous ODEs with discontinuous forcing by iterating between neural-network smoothing of the input and Levenberg-Marquardt parameter fitting, recovering true parameters where standard methods fail.