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.
- Kasun Bandara, Hansika Hewamalage, Yuan-Hao Liu, Yanfei Kang, Christoph Bergmeir (2020) Transfer Learning Schemes for Global Forecasting Models using Recurrent Neural Networks. In: 40th International Symposium on Forecasting (ISF) 2020, October 26 - 28, Virtual (Rio de Janeiro, Brazil). Abstract bib
- Kasun Bandara, Christoph Bergmeir, Sam Campbell, Debbie Scott, Dan Lubman (2020) Towards Accurate Predictions and Causal `What-if' Analyses for Planning and Policy-making: A Case Study in Emergency Medical Services Demand. In: International Joint Conference on Neural Networks (IJCNN), 19 - 24 July, 2020, Glasgow (UK) (forthcoming). Abstract pdf bib
- Chang Wei Tan, Christoph Bergmeir, Francois Petitjean, Geoffrey I. Webb (2020) Time Series Regression. In: Working Paper. Abstract pdf bib
- Rakshitha Godahewa, Chang Deng, Arnaud Prouzeau, Christoph Bergmeir (2020) Simulation and Optimisation of Air Conditioning Systems using Machine Learning. In: Working Paper. Abstract pdf bib
- Rakshitha Godahewa, Trevor Yann, Christoph Bergmeir, Francois Petitjean (2020) Seasonal Averaged One-Dependence Estimators: A Novel Algorithm to Address Seasonal Concept Drift in High-Dimensional Stream Classification. In: International Joint Conference on Neural Networks (IJCNN), 19 - 24 July, 2020, Glasgow (UK) (forthcoming). Abstract pdf bib