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Ziming Wang

5 papers hereh-index 9337 citations18 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author2
  • middle author2

Across the 4 of 5 papers where every author was matched, so the position is known.

fields
  • cs.NE4
  • cs.CV1
same name
  • Ziming Wang — 20 papers, h 7
  • Ziming Wang — 11 papers, h 8
  • Ziming Wang — 9 papers, h 5
  • Ziming Wang — 7 papers, h 5
  • Ziming Wang — 4 papers, h 1
  • Ziming Wang — 4 papers, h 1

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20222025
most citedTowards Lossless ANN-SNN Conversion under Ultra-Low Latency with Dual-Phase Optimization

31 citations · 33 across the 4 of their papers we have counts for

collaborators
Showing cs.NEShow all

4 papers · 1 filter

cs.NE2025

ASRC-SNN: Adaptive Skip Recurrent Connection Spiking Neural Network

Shang Xu, Jiayu Zhang, Ziming Wang +3

In recent years, Recurrent Spiking Neural Networks (RSNNs) have shown promising potential in long-term temporal modeling. Many studies focus on improving neuron models and also int…

cs.NE2024

GRSN: Gated Recurrent Spiking Neurons for POMDPs and MARL

Lang Qin, Ziming Wang, Runhao Jiang +2

Spiking neural networks (SNNs) are widely applied in various fields due to their energy-efficient and fast-inference capabilities. Applying SNNs to reinforcement learning (RL) can…

cs.NE2023

Neuromorphic Auditory Perception by Neural Spiketrum

Huajin Tang, Pengjie Gu, Jayawan Wijekoon +4

Neuromorphic computing holds the promise to achieve the energy efficiency and robust learning performance of biological neural systems. To realize the promised brain-like intellige…

cs.NE2022★ 31 cited

Towards Lossless ANN-SNN Conversion under Ultra-Low Latency with Dual-Phase Optimization

Ziming Wang, Shuang Lian, Yuhao Zhang +3

Spiking neural networks (SNNs) operating with asynchronous discrete events show higher energy efficiency with sparse computation. A popular approach for implementing deep SNNs is A…

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