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Explores style transfer, image translation, self-supervised learning, video prediction, and image description generation using deep learning techniques.
Covers MuZero, a model that learns to predict rewards and actions iteratively, achieving state-of-the-art performance in board games and Atari video games.
Covers the concept of gradient descent in scalar cases, focusing on finding the minimum of a function by iteratively moving in the direction of the negative gradient.
Explores safe learning in robotics, covering the state of the art, open challenges, and vision in the field, emphasizing the importance of interdisciplinary collaboration.
Explores environmental computational science and earth observation through accurate deep learning models for monitoring, integrating domain knowledge in species models, and enhancing image search.
Explores socially-aware AI for last-mile mobility, focusing on understanding social etiquettes, anticipating behaviors, and forecasting crowd movements.