On neural differential equations

On neural differential equations

<p>The conjoining of dynamical systems and deep learning has become a topic of great interest. In particular, neural differential equations (NDEs) demonstrate that neural networks and differential equation are two sides of the same coin. Traditional parameterised differential equations are a s...

Πλήρης περιγραφή

Λεπτομέρειες βιβλιογραφικής εγγραφής
Κύριος συγγραφέας:	Kidger, P
Άλλοι συγγραφείς:	Lyons, T
Μορφή:	Thesis
Γλώσσα:	English
Έκδοση:	2021
Θέματα:	Machine learning Deep learning (Machine learning) Stochastic differential equations Differential equations

Παρόμοια τεκμήρια

Learning nonlinear integral operators via recurrent neural networks and its application in solving integro-differential equations
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Data-driven simulation of ammonia combustion using neural ordinary differential equations (NODE)
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Stochastic differential equation for two-phase growth model /
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Simulation and inference for stochastic differential equations : with R examples /
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Neural modal ordinary differential equations: Integrating physics-based modeling with neural ordinary differential equations for modeling high-dimensional monitored structures
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Έκδοση: (2022-01-01)

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Modified two-step method for stochastic differential equation's parameter estimation /
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Modified two-step method for stochastic differential equation's parameter estimation /
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Stochastic partial differential equations /
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Data mining and mathematical models in cancer prognosis and prediction
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An Efficient Method for Solving Two-Dimensional Partial Differential Equations with the Deep Operator Network
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Fault Diagnosis via Neural Ordinary Differential Equations
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Theory of stochastic differential equations with jumps and applications : mathematical and analytical techniques with applications to engineering /
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