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La-MAML: Look-Ahead Meta-Learning for Continual Learning

In this work we develop a gradient-based meta-learning algorithm for efficient, online continual learning, that is robust and scalable to real-world visual benchmarks.

Learning to Prevent Monocular SLAM Failure using Reinforcement Learning

In this work, we develop a novel formulation based on Reinforcement Learning that generates fail safe trajectories while using Monocular SLAM for localization.