Jeonghwan-Cheon

lob-deep-learning

Implementation of various deep learning models for limit order book. DeepLOB (Zhang et al., 2018), TransLOB (Wallbridge, 2020), DeepFolio (Sangadiev et al., 2020), etc.

lob-world-models

Implementation of the paper <Model-based Reinforcement Learning for Predictions and Control for Limit Order Books (Wei et al., J.P. Morgan AI Research, 2019)>.

off-renderer

Render the CAD file (.off) of a object to a low-level feature controlled image under various types of transformation.

random-dot-motion

Web-based demo of random dot motion task for perceptual decision making (Britten et al., 1992)

SuperDuperTradingBot

Invariance

Source code for the paper <Invariance of object detection in untrained deep neural networks>. https://doi.org/10.3389/fncom.2022.1030707

Jeonghwan-Cheon/lob-deep-learning

Implementation of various deep learning models for limit order book. DeepLOB (Zhang et al., 2018), TransLOB (Wallbridge, 2020), DeepFolio (Sangadiev et al., 2020), etc.

Jeonghwan-Cheon/lob-world-models

Implementation of the paper <Model-based Reinforcement Learning for Predictions and Control for Limit Order Books (Wei et al., J.P. Morgan AI Research, 2019)>.

Jeonghwan-Cheon/off-renderer

Render the CAD file (.off) of a object to a low-level feature controlled image under various types of transformation.

Jeonghwan-Cheon/random-dot-motion

Web-based demo of random dot motion task for perceptual decision making (Britten et al., 1992)