My PhD student Dilini Sewwandi Rajapaksha and I made first place in the FUZZ-IEEE Explainable Energy Prediction Competition. The winners were announced at the IEEE International Conference on Fuzzy Systems, Luxembourg, 2021.
We proposed a novel algorithm to provide Local Interpretable Model-agnostic Rule-based Explanations for Forecasting, a paper and more descriptions will be available hopefully soon.
We’ve just launched the IEEE-CIS Technical Challenge on Predict+Optimize for Renewable Energy Scheduling, with US$20k in prize money. You’ll need to forecast energy demand and solar power production for a couple of buildings on the Monash Clayton campus, and then use the forecasts to optimally schedule lectures and battery charging/discharging. We’re looking forward to your great submissions!
More information is here
We have put together a new time series data repository for forecasting. It is dedicated to sets of series for cross-learning/global modelling, and to single but very long series (the longest ones over 7 million data points). We were also not too happy with any existing data format, so we developed a new one and we think it is quite useful and versatile.
Paper link: https://arxiv.org/abs/2105.06643
Congratulations to my PhD students Kasun, Hansika, and Rakshitha for their 4th place in the IEEE-CIS Technical Challenge on Energy Prediction from Smart Meter Data
Well done! Kasun describes some of the methodology here
Also congratulations to Alex Dokumentov for his 6th place (3rd in terms of accuracy).
We have released the Neural Prophet software, a reimplementation of “prophet” in PyTorch. It is joint work with Facebook and Stanford University.
The code is here
I’m giving a 2.5 hour tutorial at ACML2020 on Forecasting for Data Scientists, covering all about forecasting that Data Scientists and Machine Learners should know.
A team of 4 Monash PhD students, three of whom I supervise (Kasun Bandara, Rakshitha Godahewa and Hansika Hewamalage) have achieved a 17th place in the M5 forecasting competition, with over 5000 participants. Congratulations!