Search Results for author: Jie Fang

Found 5 papers, 0 papers with code

A Map-matching Algorithm with Extraction of Multi-group Information for Low-frequency Data

no code implementations18 Sep 2022 Jie Fang, Xiongwei Wu, DianChao Lin, Mengyun Xu, Huahua Wu, Xuesong Wu, Ting Bi

In addition, there are a large amount of other data, e. g., other vehicles' state and past prediction results, but it is hard to extract useful information for matching maps and inferring paths.

Neural Network-based Automatic Factor Construction

no code implementations14 Aug 2020 Jie Fang, Jian-Wu Lin, Shu-Tao Xia, Yong Jiang, Zhikang Xia, Xiang Liu

This paper proposes Neural Network-based Automatic Factor Construction (NNAFC), a tailored neural network framework that can automatically construct diversified financial factors based on financial domain knowledge and a variety of neural network structures.

Time Series Time Series Analysis

Prior knowledge distillation based on financial time series

no code implementations16 Jun 2020 Jie Fang, Jian-Wu Lin

In this paper, we propose to use neural networks to represent these indicators and train a large network constructed of smaller networks as feature layers to fine-tune the prior knowledge represented by the indicators.

Knowledge Distillation Time Series +1

Alpha Discovery Neural Network based on Prior Knowledge

no code implementations26 Dec 2019 Jie Fang, Shu-Tao Xia, Jian-Wu Lin, Zhikang Xia, Xiang Liu, Yong Jiang

This paper proposes Alpha Discovery Neural Network (ADNN), a tailored neural network structure which can automatically construct diversified financial technical indicators based on prior knowledge.

Time Series Time Series Analysis

Automatic Financial Feature Construction

no code implementations8 Dec 2019 Jie Fang, Shu-Tao Xia, Jian-Wu Lin, Yong Jiang

According to neural network universal approximation theorem, pre-training can conduct a more effective and explainable evolution process.

Data Augmentation Time Series Analysis

Cannot find the paper you are looking for? You can Submit a new open access paper.