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  "author": "Luxuan Yang",
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  "author": "Luxuan Yang",
            
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  "defined_in": "https://doi.org/10.48550/arXiv.2111.13164",
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  "defined_in": "https://doi.org/10.48550/arXiv.2111.13164",
            
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  "doi": "10.57702/40tsf4mc",
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  "doi": "10.57702/40tsf4mc",
            
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  "doi_date_published": "2024-12-03",
            
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  "extra_authors": [
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  "extra_authors": [
            
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    {
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    {
            
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      "extra_author": "Ting Gao",
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      "extra_author": "Ting Gao",
            
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      "orcid": ""
            
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    },
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    {
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      "extra_author": "Yubin Lu",
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      "extra_author": "Yubin Lu",
            
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      "orcid": ""
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      "orcid": ""
            
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    },
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    },
            
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    {
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      "extra_author": "Jinqiao Duan",
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      "extra_author": "Jinqiao Duan",
            
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      "orcid": ""
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      "orcid": ""
            
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    },
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    {
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      "extra_author": "Tao Liu",
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      "extra_author": "Tao Liu",
            
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      "orcid": ""
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      "orcid": ""
            
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      "title": "Stochastic Differential Equations"
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l-network-sde-models-with-applications-to-financial-data-forecasting",
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l-network-sde-models-with-applications-to-financial-data-forecasting",
            
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  "notes": "The dataset used in this paper is a collection of 
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  "notes": "The dataset used in this paper is a collection of 
            
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stochastic differential equations with drift and diffusion 
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stochastic differential equations with drift and diffusion 
            
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coefficients approximated by neural networks to predict the trend of 
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coefficients approximated by neural networks to predict the trend of 
            
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chaotic time series.",
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chaotic time series.",
            
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      "name": "Stochastic Differential Equations",
            
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  "title": "Neural Network SDE Models with Applications to Financial 
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Data Forecasting",
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Data Forecasting",
            
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}