Sequence Models

Introduction Vision forecasting is something I’ve been fascinated with so this post serves as a reflection of my understanding. This post will take you through the latest advancements in deep learning techniques used for sequential modelling, in particular with the use case of time-series vision forecasting. I’ll start with the ideas behind staple architectures, like a vanilla RNN, LSTM, and GRU, and then discuss the advancements made by their successors and why/how each new development did better than the previous one....

Overview Climatehack.ai was an international hackathon themed around fighting climate change. This post will dissect some of the thought process behind our decisions and also show methods we used to build our solution. Much credit goes to my teammates Tony Liu and Andy Cai. Background Better near-term forecasting of solar electricity generation will enable electricity grid operators around the world to do a better job of scheduling their grids. For example, the UK National Energy Grid Operator currently use a combination of solar and natural gas sources to generate power....