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20182026
most citedGate-tunable van der Waals heterostructure for reconfigurable neural network vision sensor

456 citations · 868 across the 23 of their papers we have counts for

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7 papers · 1 filter

cs.ET2026

Parameter Efficient Machine Unlearning on Hybrid Resistive Memory based Compute-in-Memory Accelerators

Ning Lin, Jichang Yang, Yangu He +17

Resistive memory compute-in-memory accelerators provide energy efficient analogue matrix vector multiplication for neural network inference, but frequent reprogramming of analogue…

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.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.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…

cs.ET2018★ 400 cited

Long short-term memory networks in memristor crossbars

Can Li, Zhongrui Wang, Mingyi Rao +14

Recent breakthroughs in recurrent deep neural networks with long short-term memory (LSTM) units has led to major advances in artificial intelligence. State-of-the-art LSTM models w…