263 citations · 737 across the 28 of their papers we have counts for
7 papers · 1 filter
On Realization of Intelligent Decision-Making in the Real World: A Foundation Decision Model Perspective
Ying Wen, Ziyu Wan, Ming Zhou +7
The pervasive uncertainty and dynamic nature of real-world environments present significant challenges for the widespread implementation of machine-driven Intelligent Decision-Maki…
Multi-Agent Feedback Enabled Neural Networks for Intelligent Communications
Fanglei Sun, Yang Li, Ying Wen +4
In the intelligent communication field, deep learning (DL) has attracted much attention due to its strong fitting ability and data-driven learning capability. Compared with the typ…
Cross-Utterance Conditioned VAE for Non-Autoregressive Text-to-Speech
Yang Li, Cheng Yu, Guangzhi Sun +6
Modelling prosody variation is critical for synthesizing natural and expressive speech in end-to-end text-to-speech (TTS) systems. In this paper, a cross-utterance conditional VAE…
Multi-Agent Reinforcement Learning is a Sequence Modeling Problem
Muning Wen, Jakub Grudzien Kuba, Runji Lin +4
Large sequence model (SM) such as GPT series and BERT has displayed outstanding performance and generalization capabilities on vision, language, and recently reinforcement learning…
Application of Lie Group-based Neural Network Method to Nonlinear Dynamical Systems
Ying Wen, Temuer Chaolu
In this paper, a Lie group-based neural network method is proposed for solving initial value problems of non linear dynamics. Due to its single-layer structure (MLP), the approach…
Solving the Initial Value Problem of Ordinary Differential Equations by Lie Group based Neural Network Method
Ying Wen, Temuer Chaolu, Xiangsheng Wang
To combine a feedforward neural network (FNN) and Lie group (symmetry) theory of differential equations (DEs), an alternative artificial NN approach is proposed to solve the initia…
Efficient Policy Space Response Oracles
Ming Zhou, Jingxiao Chen, Ying Wen +4
Policy Space Response Oracle methods (PSRO) provide a general solution to learn Nash equilibrium in two-player zero-sum games but suffer from two drawbacks: (1) the computation ine…