Zeyu Liu

Affiliations:
  • Universiy of Southern California, Los Angeles, CA, USA


According to our database1, Zeyu Liu authored at least 12 papers between 2022 and 2024.

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

Timeline

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Bibliography

2024
LMUFormer: Low Complexity Yet Powerful Spiking Model With Legendre Memory Units.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

Can we get the best of both Binary Neural Networks and Spiking Neural Networks for Efficient Computer Vision?
Proceedings of the Twelfth International Conference on Learning Representations, 2024

Training Ultra-Low-Latency Spiking Neural Networks from Scratch.
Proceedings of the IEEE International Conference on Acoustics, 2024

AFLoRA: Adaptive Freezing of Low Rank Adaptation in Parameter Efficient Fine-Tuning of Large Models.
Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics, 2024

2023
When Bio-Inspired Computing meets Deep Learning: Low-Latency, Accurate, & Energy-Efficient Spiking Neural Networks from Artificial Neural Networks.
CoRR, 2023

Spiking Neural Networks with Dynamic Time Steps for Vision Transformers.
CoRR, 2023

Enabling ISPless Low-Power Computer Vision.
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2023

Bridging the Gap Between Spiking Neural Networks & LSTMs for Latency & Energy Efficiency.
Proceedings of the IEEE/ACM International Symposium on Low Power Electronics and Design, 2023

In-Sensor & Neuromorphic Computing Are all You Need for Energy Efficient Computer Vision.
Proceedings of the IEEE International Conference on Acoustics, 2023

2022
Hoyer regularizer is all you need for ultra low-latency spiking neural networks.
CoRR, 2022

Enabling ISP-less Low-Power Computer Vision.
CoRR, 2022

P<sup>2</sup>M-DeTrack: Processing-in-Pixel-in-Memory for Energy-efficient and Real-Time Multi-Object Detection and Tracking.
Proceedings of the 30th IFIP/IEEE 30th International Conference on Very Large Scale Integration, 2022


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