3 citations · 4 across the 8 of their papers we have counts for
4 papers · 1 filter
Hardware-accelerated graph neural networks: an alternative approach for neuromorphic event-based audio classification and keyword spotting on SoC FPGA
Kamil Jeziorek, Piotr Wzorek, Krzysztof Blachut +6
As the volume of data recorded by embedded edge sensors increases, particularly from neuromorphic devices producing discrete event streams, there is a growing need for hardware-awa…
Bayesian continual learning and forgetting in neural networks
Djohan Bonnet, Kellian Cottart, Tifenn Hirtzlin +4
Biological synapses effortlessly balance memory retention and flexibility, yet artificial neural networks still struggle with the extremes of catastrophic forgetting and catastroph…
Hardware-Accelerated Event-Graph Neural Networks for Low-Latency Time-Series Classification on SoC FPGA
Hiroshi Nakano, Krzysztof Blachut, Kamil Jeziorek +6
As the quantities of data recorded by embedded edge sensors grow, so too does the need for intelligent local processing. Such data often comes in the form of time-series signals, b…
Bayesian Metaplasticity from Synaptic Uncertainty
Djohan Bonnet, Tifenn Hirtzlin, Tarcisius Januel +3
Catastrophic forgetting remains a challenge for neural networks, especially in lifelong learning scenarios. In this study, we introduce MEtaplasticity from Synaptic Uncertainty (ME…