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Found 3 papers, 1 papers with code
Characterizing Lookahead Dynamics of Smooth Games
As multi-agent systems proliferate in machine learning research, games have attracted much attention as a framework to understand optimization of multiple interacting objectives.
A Neural Dirichlet Process Mixture Model for Task-Free Continual Learning
Despite the growing interest in continual learning, most of its contemporary works have been studied in a rather restricted setting where tasks are clearly distinguishable, and task boundaries are known during training.
Harmonizing Maximum Likelihood with GANs for Multimodal Conditional Generation
Recent advances in conditional image generation tasks, such as image-to-image translation and image inpainting, are largely accounted to the success of conditional GAN models, which are often optimized by the joint use of the GAN loss with the reconstruction loss.
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