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

2 citations · 4 across the 8 of their papers we have counts for

collaborators

10 papers

cs.ET2024★ 1 cited

Topology Optimization of Random Memristors for Input-Aware Dynamic SNN

Bo Wang, Shaocong Wang, Ning Lin +12

There is unprecedented development in machine learning, exemplified by recent large language models and world simulators, which are artificial neural networks running on digital co…

cs.AR2024

Dynamic neural network with memristive CIM and CAM for 2D and 3D vision

Yue Zhang, Woyu Zhang, Shaocong Wang +14

The brain is dynamic, associative and efficient. It reconfigures by associating the inputs with past experiences, with fused memory and processing. In contrast, AI models are stati…

cs.CR2024

Older and Wiser: The Marriage of Device Aging and Intellectual Property Protection of Deep Neural Networks

Ning Lin, Shaocong Wang, Yue Zhang +6

Deep neural networks (DNNs), such as the widely-used GPT-3 with billions of parameters, are often kept secret due to high training costs and privacy concerns surrounding the data u…

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.ET2024

Efficient and accurate neural field reconstruction using resistive memory

Yifei Yu, Shaocong Wang, Woyu Zhang +16

Human beings construct perception of space by integrating sparse observations into massively interconnected synapses and neurons, offering a superior parallelism and efficiency. Re…

cs.AR2024

Resistive Memory-based Neural Differential Equation Solver for Score-based Diffusion Model

Jichang Yang, Hegan Chen, Jia Chen +19

Human brains image complicated scenes when reading a novel. Replicating this imagination is one of the ultimate goals of AI-Generated Content (AIGC). However, current AIGC methods,…

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…