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You searched for `+publisher:"Delft University of Technology" +contributor:("Borovykh, Anastasia")`

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Delft University of Technology

1. van der Meer, Remco (author). Solving Partial Differential Equations with Neural Networks.

Degree: 2019, Delft University of Technology

URL: http://resolver.tudelft.nl/uuid:c77e1bcc-7212-4234-af34-6586b628ab1c

►

Recent works have shown that neural networks can be employed to solve partial differential equations, bringing rise to the framework of physics informed neural networks.The… (more)

Subjects/Keywords: Partial Differential Equations; Neural Networks; Deep Learning; numerical methods

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^{th} Edition):

van der Meer, R. (. (2019). Solving Partial Differential Equations with Neural Networks. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:c77e1bcc-7212-4234-af34-6586b628ab1c

Chicago Manual of Style (16^{th} Edition):

van der Meer, Remco (author). “Solving Partial Differential Equations with Neural Networks.” 2019. Masters Thesis, Delft University of Technology. Accessed December 05, 2020. http://resolver.tudelft.nl/uuid:c77e1bcc-7212-4234-af34-6586b628ab1c.

MLA Handbook (7^{th} Edition):

van der Meer, Remco (author). “Solving Partial Differential Equations with Neural Networks.” 2019. Web. 05 Dec 2020.

Vancouver:

van der Meer R(. Solving Partial Differential Equations with Neural Networks. [Internet] [Masters thesis]. Delft University of Technology; 2019. [cited 2020 Dec 05]. Available from: http://resolver.tudelft.nl/uuid:c77e1bcc-7212-4234-af34-6586b628ab1c.

Council of Science Editors:

van der Meer R(. Solving Partial Differential Equations with Neural Networks. [Masters Thesis]. Delft University of Technology; 2019. Available from: http://resolver.tudelft.nl/uuid:c77e1bcc-7212-4234-af34-6586b628ab1c

Delft University of Technology

2. Hoogendoorn, Jasper (author). Sequential Monte Carlo method for training Neural Networks on non-stationary time series.

Degree: 2019, Delft University of Technology

URL: http://resolver.tudelft.nl/uuid:659e9fd5-d251-46fe-8455-3a17bdd4f48c

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In this thesis, we study the sequential Monte Carlo method for training neural networks in the context of time series forecasting. Sequential Monte Carlo can… (more)

Subjects/Keywords: sequential Monte Carlo; Neural Networks; Time Series Forecasting; Convolutional Neural Network

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^{th} Edition):

Hoogendoorn, J. (. (2019). Sequential Monte Carlo method for training Neural Networks on non-stationary time series. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:659e9fd5-d251-46fe-8455-3a17bdd4f48c

Chicago Manual of Style (16^{th} Edition):

Hoogendoorn, Jasper (author). “Sequential Monte Carlo method for training Neural Networks on non-stationary time series.” 2019. Masters Thesis, Delft University of Technology. Accessed December 05, 2020. http://resolver.tudelft.nl/uuid:659e9fd5-d251-46fe-8455-3a17bdd4f48c.

MLA Handbook (7^{th} Edition):

Hoogendoorn, Jasper (author). “Sequential Monte Carlo method for training Neural Networks on non-stationary time series.” 2019. Web. 05 Dec 2020.

Vancouver:

Hoogendoorn J(. Sequential Monte Carlo method for training Neural Networks on non-stationary time series. [Internet] [Masters thesis]. Delft University of Technology; 2019. [cited 2020 Dec 05]. Available from: http://resolver.tudelft.nl/uuid:659e9fd5-d251-46fe-8455-3a17bdd4f48c.

Council of Science Editors:

Hoogendoorn J(. Sequential Monte Carlo method for training Neural Networks on non-stationary time series. [Masters Thesis]. Delft University of Technology; 2019. Available from: http://resolver.tudelft.nl/uuid:659e9fd5-d251-46fe-8455-3a17bdd4f48c

Delft University of Technology

3. Jonker, Hendrik (author). Valuation of natural gas storage contracts with the COS method.

Degree: 2019, Delft University of Technology

URL: http://resolver.tudelft.nl/uuid:2a29f2c2-20c1-4a6e-8a7e-bb05662fd844

► Since the liberalization of the energy markets, the storage of energy is decoupled from the production and sales. In Western-Europe the storage of natural gas…
(more)

Subjects/Keywords: COS method; Gas storage valuation; Adjoint expansion

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^{th} Edition):

Jonker, H. (. (2019). Valuation of natural gas storage contracts with the COS method. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:2a29f2c2-20c1-4a6e-8a7e-bb05662fd844

Chicago Manual of Style (16^{th} Edition):

Jonker, Hendrik (author). “Valuation of natural gas storage contracts with the COS method.” 2019. Masters Thesis, Delft University of Technology. Accessed December 05, 2020. http://resolver.tudelft.nl/uuid:2a29f2c2-20c1-4a6e-8a7e-bb05662fd844.

MLA Handbook (7^{th} Edition):

Jonker, Hendrik (author). “Valuation of natural gas storage contracts with the COS method.” 2019. Web. 05 Dec 2020.

Vancouver:

Jonker H(. Valuation of natural gas storage contracts with the COS method. [Internet] [Masters thesis]. Delft University of Technology; 2019. [cited 2020 Dec 05]. Available from: http://resolver.tudelft.nl/uuid:2a29f2c2-20c1-4a6e-8a7e-bb05662fd844.

Council of Science Editors:

Jonker H(. Valuation of natural gas storage contracts with the COS method. [Masters Thesis]. Delft University of Technology; 2019. Available from: http://resolver.tudelft.nl/uuid:2a29f2c2-20c1-4a6e-8a7e-bb05662fd844

Delft University of Technology

4. Verberne, Stijn (author). Estimating model uncertainty for conditional prepayment rate predictions using artificial neural networks with dropout.

Degree: 2019, Delft University of Technology

URL: http://resolver.tudelft.nl/uuid:69fbfb01-a0a1-47f2-aa38-a0d93e0eb330

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Clients with a mortgage loan may prepay a part of their loan before the contractual date. This is called prepayment. In the case of a… (more)

Subjects/Keywords: Artificial Neural Networks; Dropout; Uncertainty; Mortgages; Conditional Prepayment Rate

Record Details Similar Records

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^{th} Edition):

Verberne, S. (. (2019). Estimating model uncertainty for conditional prepayment rate predictions using artificial neural networks with dropout. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:69fbfb01-a0a1-47f2-aa38-a0d93e0eb330

Chicago Manual of Style (16^{th} Edition):

Verberne, Stijn (author). “Estimating model uncertainty for conditional prepayment rate predictions using artificial neural networks with dropout.” 2019. Masters Thesis, Delft University of Technology. Accessed December 05, 2020. http://resolver.tudelft.nl/uuid:69fbfb01-a0a1-47f2-aa38-a0d93e0eb330.

MLA Handbook (7^{th} Edition):

Verberne, Stijn (author). “Estimating model uncertainty for conditional prepayment rate predictions using artificial neural networks with dropout.” 2019. Web. 05 Dec 2020.

Vancouver:

Verberne S(. Estimating model uncertainty for conditional prepayment rate predictions using artificial neural networks with dropout. [Internet] [Masters thesis]. Delft University of Technology; 2019. [cited 2020 Dec 05]. Available from: http://resolver.tudelft.nl/uuid:69fbfb01-a0a1-47f2-aa38-a0d93e0eb330.

Council of Science Editors:

Verberne S(. Estimating model uncertainty for conditional prepayment rate predictions using artificial neural networks with dropout. [Masters Thesis]. Delft University of Technology; 2019. Available from: http://resolver.tudelft.nl/uuid:69fbfb01-a0a1-47f2-aa38-a0d93e0eb330