New conference paper accepted for the IEEE International Conference on Machine Learning and Applications (ICMLA) 2022

In the article, "Unified Autoencoder with Task Embeddings for Multi-Task Learning in Renewable Power Forecasting", Chandana Priya Nivarthi, Stephan Vogt and Bernhard Sick propose the use of combination of autoencoder and task embeddings for multi-task and transfer learning scenarios in renewable power forecasting.