3 papers
cs.NE2026
Energy-Efficient Implementation of Spiking Recurrent Cells on FPGA
Pascal Harmeling, Florent De Geeter, Guillaume Drion
Spiking Neural Networks (SNNs) can reduce energy consumption compared to conventional Artificial Neural Networks (ANNs) when spiking activity is sparse and the neuron model is hard…
cs.LG2026
Parallelizable memory recurrent units
Florent De Geeter, Gaspard Lambrechts, Damien Ernst +1
With the emergence of massively parallel processing units, parallelization has become a desirable property for new sequence models. The ability to parallelize the processing of seq…
cs.LG2026
On the Importance of Multistability for Horizon Generalization in Reinforcement Learning
Asad Bakija, Florent De Geeter, Julien Brandoit +2
In reinforcement learning (RL), agents acting in partially observable Markov decision processes (POMDPs) must rely on memory, typically encoded in a recurrent neural network (RNN),…