Plastic Elastic πŸ•Έ


Differentiable Plasticity looks really interesting. Basically a “plastic” weight is added to every connection within a neural network that can change over time as leaning continues. You keep the static weights from training like all other neural nets but have this additional weight changing as needed. πŸŽ›

The idea is based on “synaptic plasticity”. No, that’s not a jam band album. It’s a feature of the brain that allows connections between synapses to change over time. 🧠

This could obviously be immensely helpful for models to actually learn over time. The early results look impressive. I also wonder if this would help minimize the risk of overfitting? πŸ€”

Src: Towards Data Science