LCN-An Experimental initiative

LCN-An Experimental initiative | originally published on havric

Time-traveling algorithms sipping coffee, predicting the future. But wait, there’s a new kid on the block — the Liquid Capsule Network for Time Series Forecasting (LCN-TSF). It’s like James Bond meets data science, decoding tricky patterns. Buckle up, because we’re diving into LCN-TSF’s secret lair!

Meet the LCN-TSF

The LCN-TSF model is built with some advanced but cool components:

1. Liquid State Machine (LSM): Think of it as a neural network with a splash of chaos, perfect for handling tricky temporal patterns.
2. Capsule Networks: These preserve spatial hierarchies and dynamic routing, making sure we capture all the juicy details in the data.
3. LSTM-based Decoder: An LSTM layer that decodes the processed data and makes predictions.

What motivated me

I’m driven by curiosity and a love for making things interesting (and a bit funny). Time series forecasting can be dull, but combining spiking neurons and capsule networks sounded exciting. Turns out, it’s powerful too! So here we are, exploring the cool world of LCN-TSF!

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