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20212024
most citedResistive memory-based zero-shot liquid state machine for multimodal event data learning

2 citations · 3 across the 5 of their papers we have counts for

collaborators

5 papers

cs.AR2024

Continuous-Time Digital Twin with Analogue Memristive Neural Ordinary Differential Equation Solver

Hegan Chen, Jichang Yang, Jia Chen +20

Digital twins, the cornerstone of Industry 4.0, replicate real-world entities through computer models, revolutionising fields such as manufacturing management and industrial automa…

cs.LG2023

Random resistive memory-based deep extreme point learning machine for unified visual processing

Shaocong Wang, Yizhao Gao, Yi Li +21

Visual sensors, including 3D LiDAR, neuromorphic DVS sensors, and conventional frame cameras, are increasingly integrated into edge-side intelligent machines. Realizing intensive m…

cs.ET2023

Pruning random resistive memory for optimizing analogue AI

Yi Li, Songqi Wang, Yaping Zhao +17

The rapid advancement of artificial intelligence (AI) has been marked by the large language models exhibiting human-like intelligence. However, these models also present unpreceden…

cs.ET2023★ 2 cited

Resistive memory-based zero-shot liquid state machine for multimodal event data learning

Ning Lin, Shaocong Wang, Yi Li +19

The human brain is a complex spiking neural network (SNN), capable of learning multimodal signals in a zero-shot manner by generalizing existing knowledge. Remarkably, it maintains…

cs.ET2021★ 1 cited

Echo state graph neural networks with analogue random resistor arrays

Shaocong Wang, Yi Li, Dingchen Wang +13

Recent years have witnessed an unprecedented surge of interest, from social networks to drug discovery, in learning representations of graph-structured data. However, graph neural…