42 citations · 84 across the 6 of their papers we have counts for
6 papers
Forex Trading Volatility Prediction using Neural Network Models
Shujian Liao, Jian Chen, Hao Ni
In this paper, we investigate the problem of predicting the future volatility of Forex currency pairs using the deep learning techniques. We show step-by-step how to construct the…
Sig-Wasserstein GANs for Time Series Generation
Hao Ni, Lukasz Szpruch, Marc Sabate-Vidales +3
Synthetic data is an emerging technology that can significantly accelerate the development and deployment of AI machine learning pipelines. In this work, we develop high-fidelity t…
Logsig-RNN: a novel network for robust and efficient skeleton-based action recognition
Shujian Liao, Terry Lyons, Weixin Yang +2
This paper contributes to the challenge of skeleton-based human action recognition in videos. The key step is to develop a generic network architecture to extract discriminative fe…
A thorough introduction to non-relativistic matrix mechanics in multi-qudit systems with a study on quantum entanglement and quantum quantifiers
Lucas Camponogara Viera, Shu-Hsien Liao
Quantum computing is among the most far-reaching technologies of the 21st century, tackling challenges at the cutting edge of physics. This new paradigm in computer science harness…
Conditional Sig-Wasserstein GANs for Time Series Generation
Shujian Liao, Hao Ni, Lukasz Szpruch +3
Generative adversarial networks (GANs) have been extremely successful in generating samples, from seemingly high dimensional probability measures. However, these methods struggle t…
Learning stochastic differential equations using RNN with log signature features
Shujian Liao, Terry Lyons, Weixin Yang +1
This paper contributes to the challenge of learning a function on streamed multimodal data through evaluation. The core of the result of our paper is the combination of two quite d…