Xueyuan She

Orcid: 0000-0002-7372-5366

According to our database1, Xueyuan She authored at least 13 papers between 2018 and 2023.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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PhD thesis 
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Links

On csauthors.net:

Bibliography

2023
Brain-Inspired Spatiotemporal Processing Algorithms for Efficient Event-Based Perception.
Proceedings of the Design, Automation & Test in Europe Conference & Exhibition, 2023

2022
Design and Optimization of Heterogeneous Feedforward Spiking Neural Network For Spatiotemporal Data Processing.
PhD thesis, 2022

Learning Point Processes using Recurrent Graph Network.
Proceedings of the International Joint Conference on Neural Networks, 2022

Sequence Approximation using Feedforward Spiking Neural Network for Spatiotemporal Learning: Theory and Optimization Methods.
Proceedings of the Tenth International Conference on Learning Representations, 2022

2021
A Fully Spiking Hybrid Neural Network for Energy-Efficient Object Detection.
IEEE Trans. Image Process., 2021

ScieNet: Deep learning with spike-assisted contextual information extraction.
Pattern Recognit., 2021

Reliable Edge Intelligence in Unreliable Environment.
Proceedings of the Design, Automation & Test in Europe Conference & Exhibition, 2021

2020
SAFE-DNN: A Deep Neural Network With Spike Assisted Feature Extraction For Noise Robust Inference.
Proceedings of the 2020 International Joint Conference on Neural Networks, 2020

2019
Improving Robustness of ReRAM-based Spiking Neural Network Accelerator with Stochastic Spike-timing-dependent-plasticity.
Proceedings of the International Joint Conference on Neural Networks, 2019

Fast and Low-Precision Learning in GPU-Accelerated Spiking Neural Network.
Proceedings of the Design, Automation & Test in Europe Conference & Exhibition, 2019

Design of Reliable DNN Accelerator with Un-reliable ReRAM.
Proceedings of the Design, Automation & Test in Europe Conference & Exhibition, 2019

2018
Accelerating biophysical neural network simulation with region of interest based approximation.
Proceedings of the 2018 Design, Automation & Test in Europe Conference & Exhibition, 2018

HybridNet: Integrating Model-based and Data-driven Learning to Predict Evolution of Dynamical Systems.
Proceedings of the 2nd Annual Conference on Robot Learning, 2018


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