18 citations · 20 across the 6 of their papers we have counts for
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cs.AR2024
An Event-Based Digital Compute-In-Memory Accelerator with Flexible Operand Resolution and Layer-Wise Weight/Output Stationarity
Nicolas Chauvaux, Adrian Kneip, Christoph Posch +2
Compute-in-memory (CIM) accelerators for spiking neural networks (SNNs) are promising solutions to enable s-level inference latency and ultra-low energy in edge vision applicati…
cs.CV2024★ 18 cited
EvGNN: An Event-driven Graph Neural Network Accelerator for Edge Vision
Yufeng Yang, Adrian Kneip, Charlotte Frenkel
Edge vision systems combining sensing and embedded processing promise low-latency, decentralized, and energy-efficient solutions that forgo reliance on the cloud. As opposed to con…