温州求学
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I recently stumbled upon a perplexing issue where my neural network, tasked with a regression problem, stubbornly learned to predict the average value of the dataset. After hours of meticulous investigation, I managed to close this issue.
In this blog, I’ll delve into the crux of the problem and share some insights I obtained for training neural networks till now.
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After configuring the personal github.io page, it is expected that your customized pages will be found using Google search engines. However, it is not for granted and in this Blog, we’ll show how to achieve this.
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We live within the scenes we create, not the memories we leave behind. Yet, some memories are worth documenting, for they become part of the scene when we look back once again.
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Published in Proceedings of the AAAI Symposium Series, 2023
This paper proposed a novel approach called Evolutionary Neural Network to solve option pricing problems. Evolutionary Neural Network has time-variable parameters, transforming the time-dependent PDEs into ODEs and then applying a standard ODE solver to solve it. This framework is flexible with boundary conditions and can scale up to higher dimensions, allowing pricing customized options.
Recommended citation: Li, Y., Wu, Z., & Ye, F. (2023). Evolutionary Neural Networks for Option Pricing: Multi-Assets Option and Exotic Option. Proceedings of the AAAI Symposium Series.
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Undergraduate course, University 1, Department, 2014
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Workshop, University 1, Department, 2015
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