6 citations · 6 across the 2 of their papers we have counts for
3 papers
Length-Independent State Tracking Under a Parallel Scan
Julien Brandoit, Arthur Fyon, Thomas Braipson +5
Learning robust and scalable finite-state tracking is fundamental to sequence processing. While linear recurrent neural networks (RNNs), linear attention, and state space models en…
Train Short, Act Long: Multistability and the Horizon Independence of Recurrent Policies
Asad Bakija, Florent De Geeter, Julien Brandoit +2
In partially observable reinforcement learning (RL), a decision often depends on a cue seen many steps earlier, and training at such horizons is costly. Ideally, a policy trained o…
Spike-based computation using classical recurrent neural networks
Florent De Geeter, Damien Ernst, Guillaume Drion
Spiking neural networks are a type of artificial neural networks in which communication between neurons is only made of events, also called spikes. This property allows neural netw…