Transductive Spiking Graph Neural Networks for Loihi-Reference-Cited by-同舟云学术

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Transductive Spiking Graph Neural Networks for Loihi

Published:2024-06-12 Issue: Volume: Page:608-613
ISSN:
Container-title:Proceedings of the Great Lakes Symposium on VLSI 2024
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Author:

Snyder Shay¹^ORCID,Clerico Victoria²^ORCID,Cong Guojing³^ORCID,Kulkarni Shruti⁴^ORCID,Schuman Catherine⁵^ORCID,Risbud Sumedh⁶^ORCID,Parsa Maryam⁷^ORCID

Affiliation:

1. Electrical and Computer Engineering, George Mason University, USA

2. Electrical and Computer Engineering, George Mason University, USA and Universidad Politecnica de Madrid, Spain

3. Oak Ridge National Laboratory, USA

4. Computer Science and Mathematics Division, Oak Ridge National Laboratory, USA

5. University of Tennessee - Knoxville, USA

6. Intel Labs, USA

7. George Mason University, USA

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3649476.3660366

Reference24 articles.

1. Sami Abu-El-Haija, Bryan Perozzi, Rami Al-Rfou, and Alex Alemi. 2017. Watch Your Step: Learning Graph Embeddings Through Attention. CoRR abs/1710.09599 (2017). arXiv:1710.09599http://arxiv.org/abs/1710.09599

2. Provable Neuromorphic Advantages for Computing Shortest Paths

3. TrueNorth: Design and Tool Flow of a 65 mW 1 Million Neuron Programmable Neurosynaptic Chip

4. Hyperparameter Optimization and Feature Inclusion in Graph Neural Networks for Spiking Implementation

5. Versatile feature learning with graph convolutions and graph structures

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