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Found 3 papers, 2 papers with code
Warming up recurrent neural networks to maximise reachable multistability greatly improves learning
This insight leads to the design of a novel way to initialise any recurrent cell connectivity through a procedure called "warmup" to improve its capability to learn arbitrarily long time dependencies.
A bio-inspired bistable recurrent cell allows for long-lasting memory
Standard gated cells share a layer internal state to store information at the network level, and long term memory is shaped by network-wide recurrent connection weights.
Introducing Neuromodulation in Deep Neural Networks to Learn Adaptive Behaviours
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 external world, a property that intelligent machines currently lack.
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