Search Results for author: Jing Luo

Found 13 papers, 4 papers with code

Learning a Structural Causal Model for Intuition Reasoning in Conversation

1 code implementation28 May 2023 Hang Chen, Bingyu Liao, Jing Luo, Wenjing Zhu, Xinyu Yang

Reasoning, a crucial aspect of NLP research, has not been adequately addressed by prevailing models including Large Language Model.

Causal Discovery Language Modelling +2

Asymptotic in a class of network models with an increasing sub-Gamma degree sequence

no code implementations2 Nov 2021 Jing Luo, Haoyu Wei, Xiaoyu Lei, Jiaxin Guo

For the differential privacy under the sub-Gamma noise, we derive the asymptotic properties of a class of network models with binary values with a general link function.

WakaVT: A Sequential Variational Transformer for Waka Generation

no code implementations1 Apr 2021 Yuka Takeishi, Mingxuan Niu, Jing Luo, Zhong Jin, Xinyu Yang

To further explore the creative potential of natural language generation systems in Japanese poetry creation, we propose a novel Waka generation model, WakaVT, which automatically produces Waka poems given user-specified keywords.

Text Generation

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

no code implementations13 Nov 2020 Shulei Ji, Jing Luo, Xinyu Yang

This paper attempts to provide an overview of various composition tasks under different music generation levels, covering most of the currently popular music generation tasks using deep learning.

Audio Generation Music Generation

The NANOGrav 12.5 yr Data Set: Observations and Narrowband Timing of 47 Millisecond Pulsars

no code implementations13 May 2020 Md F. Alam, Zaven Arzoumanian, Paul T. Baker, Harsha Blumer, Keith E. Bohler, Adam Brazier, Paul R. Brook, Sarah Burke-Spolaor, Keeisi Caballero, Richard S. Camuccio, Rachel L. Chamberlain, Shami Chatterjee, James M. Cordes, Neil J. Cornish, Fronefield Crawford, H. Thankful Cromartie, Megan E. DeCesar, Paul B. Demorest, Timothy Dolch, Justin A. Ellis, Robert D. Ferdman, Elizabeth C. Ferrara, William Fiore, Emmanuel Fonseca, Yhamil Garcia, Nathan Garver-Daniels, Peter A. Gentile, Deborah C. Good, Jordan A. Gusdorff, Daniel Halmrast, Jeffrey Hazboun, Kristina Islo, Ross J. Jennings, Cody Jessup, Megan L. Jones, Andrew R. Kaiser, David L. Kaplan, Luke Zoltan Kelley, Joey Shapiro Key, Michael T. Lam, T. Joseph W. Lazio, Duncan R. Lorimer, Jing Luo, Ryan S. Lynch, Dustin Madison, Kaleb Maraccini, Maura A. McLaughlin, Chiara M. F. Mingarelli, Cherry Ng, Benjamin M. X. Nguyen, David J. Nice, Timothy T. Pennucci, Nihan S. Pol, Joshua Ramette, Scott M. Ransom, Paul S. Ray, Brent J. Shapiro-Albert, Xavier Siemens, Joseph Simon, Renee Spiewak, Ingrid H. Stairs, Daniel R. Stinebring, Kevin Stovall, Joseph K. Swiggum, Stephen R. Taylor, Michael Tripepi, Michele Vallisneri, Sarah J. Vigeland, Caitlin A. Witt, Weiwei Zhu

We detail our observational methods and present a set of TOA measurements, based on "narrowband" analysis, in which many TOAs are calculated within narrow radio-frequency bands for data collected simultaneously across a wide bandwidth.

Time Series Analysis High Energy Astrophysical Phenomena Instrumentation and Methods for Astrophysics

Flow Rate Control in Smart District Heating Systems Using Deep Reinforcement Learning

no code implementations1 Dec 2019 Tinghao Zhang, Jing Luo, Ping Chen, Jie Liu

At high latitudes, many cities adopt a centralized heating system to improve the energy generation efficiency and to reduce pollution.

reinforcement-learning Reinforcement Learning (RL)

MG-VAE: Deep Chinese Folk Songs Generation with Specific Regional Style

no code implementations29 Sep 2019 Jing Luo, Xinyu Yang, Shulei Ji, Juan Li

In this paper, we propose MG-VAE, a music generative model based on VAE (Variational Auto-Encoder) that is capable of capturing specific music style and generating novel tunes for Chinese folk songs (Min Ge) in a manipulatable way.

Music Generation Multimedia Sound Audio and Speech Processing

Interactions of Fungi with Concrete: Significant Importance for Bio-Based Self-Healing Concrete

no code implementations4 Aug 2017 Jing Luo, Xiaobo Chen, Jada Crump, Hui Zhou, David G. Davies, Guangwen Zhou, Ning Zhang, Congrui Jin

The goal of this study is to explore a new self-healing concept in which fungi are used as a self-healing agent to promote calcium mineral precipitation to fill the cracks in concrete.

X-Ray Diffraction (XRD)

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