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05/02/2023
Physics-Informed Learning Using Hamiltonian Neural Networks with Output Error Noise Models
In order to make data-driven models of physical systems interpretable an...
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04/04/2023
Initialization Approach for Nonlinear State-Space Identification via the Subspace Encoder Approach
The SUBNET neural network architecture has been developed to identify no...
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11/27/2022
A Data-driven Pricing Scheme for Optimal Routing through Artificial Currencies
Mobility systems often suffer from a high price of anarchy due to the un...
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10/26/2022
Deep Subspace Encoders for Nonlinear System Identification
Using Artificial Neural Networks (ANN) for nonlinear system identificati...
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04/20/2022
Deep subspace encoders for continuous-time state-space identification
Continuous-time (CT) models have shown an improved sample efficiency dur...
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04/02/2022
Variational message passing for online polynomial NARMAX identification
We propose a variational Bayesian inference procedure for online nonline...
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10/06/2021
Deep Identification of Nonlinear Systems in Koopman Form
The present paper treats the identification of nonlinear dynamical syste...
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03/26/2021
Improved Initialization of State-Space Artificial Neural Networks
The identification of black-box nonlinear state-space models requires a ...
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12/14/2020
Non-linear State-space Model Identification from Video Data using Deep Encoders
Identifying systems with high-dimensional inputs and outputs, such as sy...
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12/14/2020
Nonlinear state-space identification using deep encoder networks
Nonlinear state-space identification for dynamical systems is most often...
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12/14/2020
System identification of biophysical neuronal models
After sixty years of quantitative biophysical modeling of neurons, the i...
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01/15/2020
A Tree Adjoining Grammar Representation for Models Of Stochastic Dynamical Systems
Model structure and complexity selection remains a challenging problem i...
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04/05/2019
