activity
20202022
most citedLearning to Simulate Unseen Physical Systems with Graph Neural Networks

6 citations · 6 across the 4 of their papers we have counts for

collaborators

6 papers

cs.SD2022

Fast-U2++: Fast and Accurate End-to-End Speech Recognition in Joint CTC/Attention Frames

Chengdong Liang, Xiao-Lei Zhang, BinBin Zhang +5

Recently, the unified streaming and non-streaming two-pass (U2/U2++) end-to-end model for speech recognition has shown great performance in terms of streaming capability, accuracy…

cs.SD2022

FusionFormer: Fusing Operations in Transformer for Efficient Streaming Speech Recognition

Xingchen Song, Di Wu, Binbin Zhang +8

The recently proposed Conformer architecture which combines convolution with attention to capture both local and global dependencies has become the \textit{de facto} backbone model…

cs.LG20226 cited

Learning to Simulate Unseen Physical Systems with Graph Neural Networks

Ce Yang, Weihao Gao, Di Wu +1

Simulation of the dynamics of physical systems is essential to the development of both science and engineering. Recently there is an increasing interest in learning to simulate the…

cs.LG2021

Unsupervised Deep Manifold Attributed Graph Embedding

Zelin Zang, Siyuan Li, Di Wu +3

Unsupervised attributed graph representation learning is challenging since both structural and feature information are required to be represented in the latent space. Existing meth…

cs.AI2021

Representation range needs for 16-bit neural network training

Valentina Popescu, Abhinav Venigalla, Di Wu +1

Deep learning has grown rapidly thanks to its state-of-the-art performance across a wide range of real-world applications. While neural networks have been trained using IEEE-754 bi…

cs.HC2020

DeepBrain: Towards Personalized EEG Interaction through Attentional and Embedded LSTM Learning

Di Wu, Huayan Wan, Siping Liu +3

The "mind-controlling" capability has always been in mankind's fantasy. With the recent advancements of electroencephalograph (EEG) techniques, brain-computer interface (BCI) resea…