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08/25/2023
In-context learning for model-free system identification
In traditional system identification, we estimate a model of an unknown ...
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04/13/2023
Neural State-Space Models: Empirical Evaluation of Uncertainty Quantification
Effective quantification of uncertainty is an essential and still missin...
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06/26/2022
Learning neural state-space models: do we need a state estimator?
In recent years, several algorithms for system identification with neura...
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01/21/2022
On the adaptation of recurrent neural networks for system identification
This paper presents a transfer learning approach which enables fast and ...
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04/20/2021
Deep learning with transfer functions: new applications in system identification
This paper presents a linear dynamical operator described in terms of a ...
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06/03/2020
dynoNet: a neural network architecture for learning dynamical systems
This paper introduces a network architecture, called dynoNet, utilizing ...
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06/03/2020
Continuous-time system identification with neural networks: model structures and fitting criteria
This paper presents tailor-made neural model structures and two custom f...
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11/29/2019