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Lifelong Generative Modeling

The case for lifelong learning Lifelong learning (also known as continual learning) is the problem of learning multiple consecutive tasks in a sequential manner where knowledge gained from previous tasks is retained and used for future learning [1]. Living in … Continue reading

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Sample-Efficient Imitation Learning via Generative Adversarial Nets

Generative Adversarial Imitation Learning (GAIL) [1] is a recent successful imitation learning architecture that exploits the adversarial training procedure introduced in Generative Adversarial Networks (GAN) [2]. Albeit successful at generating behaviours similar to those demonstrated to the agent, GAIL suffers … Continue reading

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