Fetching the paper…

Reading the bibliography…

2020

Explainable Deep Convolutional Candlestick Learner

Chen, Jun-Hao, Chen, Samuel Yen-Chi, Tsai, Yun-Cheng et al.

Original
PDF
Post on X

Understand

Candlesticks are graphical representations of price movements for a given period.

The traders can discovery the trend of the asset by looking at the candlestick patterns.
Although deep convolutional neural networks have achieved great success for recognizing the candlestick patterns, their reasoning hides inside a black box.
The traders cannot make sure what the model has learned.

Explainable Deep Convolutional Candlestick Learner · Around

Built on

Lenet-5, convolutional neural networks
Yann LeCun et al · 2015
Earlier work this paper cites.
Encoding time series as images for visual inspection and classification using tiled convolutional neural networks
Zhiguang Wang and Tim Oates · 2015
Earlier work this paper cites.

Similar

Simple black-box adversarial attacks on deep neural networks
N. Narodytska and S. Kasiviswanathan · 2017
Cited alongside, same era.
Explainable artificial intelligence: Understanding, visualizing and interpreting deep learning models
Original
Wojciech Samek, Thomas Wiegand, and Klaus-Robert Müller · 2017
Cited alongside, same era.

Then

Encoding candlesticks as images for patterns classification using convolutional neural networks
Original
Yun-Cheng Tsai, Jun-Hao Chen, and Chun-Chieh Wang · 2019
Later among the works it cites.

Beyond the bibliography

alphaXiv searches the wider corpus for related work and actual follow-ups.

Open on alphaXiv

alphaXiv is searching for related work…