25 citations · 157 across the 23 of their papers we have counts for
52 papers
QuadraLib: A Performant Quadratic Neural Network Library for Architecture Optimization and Design Exploration
Zirui Xu, Fuxun Yu, Jinjun Xiong +1
The significant success of Deep Neural Networks (DNNs) is highly promoted by the multiple sophisticated DNN libraries. On the contrary, although some work have proved that Quadrati…
Can Noise on Qubits Be Learned in Quantum Neural Network? A Case Study on QuantumFlow
Zhiding Liang, Zhepeng Wang, Junhuan Yang +4
In the noisy intermediate-scale quantum (NISQ) era, one of the key questions is how to deal with the high noise level existing in physical quantum bits (qubits). Quantum error corr…
Exploration of Quantum Neural Architecture by Mixing Quantum Neuron Designs
Zhepeng Wang, Zhiding Liang, Shanglin Zhou +3
With the constant increase of the number of quantum bits (qubits) in the actual quantum computers, implementing and accelerating the prevalent deep learning on quantum computers ar…
Large Graph Convolutional Network Training with GPU-Oriented Data Communication Architecture
Seung Won Min, Kun Wu, Sitao Huang +5
Graph Convolutional Networks (GCNs) are increasingly adopted in large-scale graph-based recommender systems. Training GCN requires the minibatch generator traversing graphs and sam…
PyTorch-Direct: Enabling GPU Centric Data Access for Very Large Graph Neural Network Training with Irregular Accesses
Seung Won Min, Kun Wu, Sitao Huang +5
With the increasing adoption of graph neural networks (GNNs) in the machine learning community, GPUs have become an essential tool to accelerate GNN training. However, training GNN…
When Machine Learning Meets Quantum Computers: A Case Study
Weiwen Jiang, Jinjun Xiong, Yiyu Shi
Along with the development of AI democratization, the machine learning approach, in particular neural networks, has been applied to wide-range applications. In different applicatio…