16 citations · 17 across the 3 of their papers we have counts for
3 papers
mGRADE: Minimal Recurrent Gating Meets Delay Convolutions for Lightweight Sequence Modeling
Tristan Torchet, Christian Metzner, Karthik Charan Raghunathan +4
Multi-timescale sequence modeling relies on capturing both local fast dynamics and global slow context; yet, maintaining these capabilities under the strict memory constraints comm…
DelGrad: Exact event-based gradients for training delays and weights on spiking neuromorphic hardware
Julian Göltz, Jimmy Weber, Laura Kriener +5
Spiking neural networks (SNNs) inherently rely on the timing of signals for representing and processing information. Incorporating trainable transmission delays, alongside synaptic…
NeuroBench: A Framework for Benchmarking Neuromorphic Computing Algorithms and Systems
Jason Yik, Korneel Van den Berghe, Douwe den Blanken +97
Neuromorphic computing shows promise for advancing computing efficiency and capabilities of AI applications using brain-inspired principles. However, the neuromorphic research fiel…