26 citations · 27 across the 3 of their papers we have counts for
3 papers
Warming up recurrent neural networks to maximise reachable multistability greatly improves learning
Gaspard Lambrechts, Florent De Geeter, Nicolas Vecoven +2
Training recurrent neural networks is known to be difficult when time dependencies become long. In this work, we show that most standard cells only have one stable equilibrium at i…
A bio-inspired bistable recurrent cell allows for long-lasting memory
Nicolas Vecoven, Damien Ernst, Guillaume Drion
Recurrent neural networks (RNNs) provide state-of-the-art performances in a wide variety of tasks that require memory. These performances can often be achieved thanks to gated recu…
Introducing Neuromodulation in Deep Neural Networks to Learn Adaptive Behaviours
Nicolas Vecoven, Damien Ernst, Antoine Wehenkel +1
Animals excel at adapting their intentions, attention, and actions to the environment, making them remarkably efficient at interacting with a rich, unpredictable and ever-changing…