activity
20192022
most citedA Comprehensive Survey on Deep Music Generation: Multi-level Representations, Algorithms, Evaluations, and Future Directions

81 citations · 112 across the 6 of their papers we have counts for

collaborators

9 papers

cs.LG20228 cited

A Review and Roadmap of Deep Learning Causal Discovery in Different Variable Paradigms

Hang Chen, Keqing Du, Xinyu Yang +1

Understanding causality helps to structure interventions to achieve specific goals and enables predictions under interventions. With the growing importance of learning causal relat…

cs.LG20212 cited

DTWSSE: Data Augmentation with a Siamese Encoder for Time Series

Xinyu Yang, Xinlan Zhang, Zhenguo Zhang +2

Access to labeled time series data is often limited in the real world, which constrains the performance of deep learning models in the field of time series analysis. Data augmentat…

cs.SD202120 cited

Review of end-to-end speech synthesis technology based on deep learning

Zhaoxi Mu, Xinyu Yang, Yizhuo Dong

As an indispensable part of modern human-computer interaction system, speech synthesis technology helps users get the output of intelligent machine more easily and intuitively, thu…

cs.CL2021

WakaVT: A Sequential Variational Transformer for Waka Generation

Yuka Takeishi, Mingxuan Niu, Jing Luo +2

Poetry generation has long been a challenge for artificial intelligence. In the scope of Japanese poetry generation, many researchers have paid attention to Haiku generation, but f…

cs.SD202081 cited

A Comprehensive Survey on Deep Music Generation: Multi-level Representations, Algorithms, Evaluations, and Future Directions

Shulei Ji, Jing Luo, Xinyu Yang

The utilization of deep learning techniques in generating various contents (such as image, text, etc.) has become a trend. Especially music, the topic of this paper, has attracted…

cs.CV2020

Back to the Future: Cycle Encoding Prediction for Self-supervised Contrastive Video Representation Learning

Xinyu Yang, Majid Mirmehdi, Tilo Burghardt

In this paper we show that learning video feature spaces in which temporal cycles are maximally predictable benefits action classification. In particular, we propose a novel learni…