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cs.LG2026
Rapid Augmentations for Time Series (RATS): A High-Performance Library for Time Series Augmentation
Wadie Skaf, Felix Kern, Aryamaan Basu Roy +3
Time series augmentation is critical for training robust deep learning models, particularly in domains where labelled data is scarce and expensive to obtain. However, existing augm…
cs.LG2022
On the Verge of Solving Rocket League using Deep Reinforcement Learning and Sim-to-sim Transfer
Marco Pleines, Konstantin Ramthun, Yannik Wegener +12
Autonomously trained agents that are supposed to play video games reasonably well rely either on fast simulation speeds or heavy parallelization across thousands of machines runnin…