206 citations · 234 across the 15 of their papers we have counts for
4 papers · 1 filter
Spatio-Temporal Wind Speed Forecasting using Graph Networks and Novel Transformer Architectures
Lars Ødegaard Bentsen, Narada Dilp Warakagoda, Roy Stenbro +1
This study focuses on multi-step spatio-temporal wind speed forecasting for the Norwegian continental shelf. The study aims to leverage spatial dependencies through the relative ph…
Deep Reinforcement Learning with Swin Transformers
Li Meng, Morten Goodwin, Anis Yazidi +1
Transformers are neural network models that utilize multiple layers of self-attention heads and have exhibited enormous potential in natural language processing tasks. Meanwhile, t…
Improving the Diversity of Bootstrapped DQN by Replacing Priors With Noise
Li Meng, Morten Goodwin, Anis Yazidi +1
Q-learning is one of the most well-known Reinforcement Learning algorithms. There have been tremendous efforts to develop this algorithm using neural networks. Bootstrapped Deep Q-…
Wind Park Power Prediction: Attention-Based Graph Networks and Deep Learning to Capture Wake Losses
Lars Ødegaard Bentsen, Narada Dilp Warakagoda, Roy Stenbro +1
With the increased penetration of wind energy into the power grid, it has become increasingly important to be able to predict the expected power production for larger wind farms. D…