Explores perception in deep learning for autonomous vehicles, covering image classification, optimization methods, and the role of representation in machine learning.
Explores model-based deep reinforcement learning, focusing on Monte Carlo Tree Search and its applications in game strategies and decision-making processes.
Explores style transfer, image translation, self-supervised learning, video prediction, and image description generation using deep learning techniques.
Explores environmental computational science and earth observation through accurate deep learning models for monitoring, integrating domain knowledge in species models, and enhancing image search.
Covers the fundamental concepts of machine learning, including classification, algorithms, optimization, supervised learning, reinforcement learning, and various tasks like image recognition and text generation.
Covers the foundational concepts of deep learning and the Transformer architecture, focusing on neural networks, attention mechanisms, and their applications in sequence modeling tasks.
Explores the EPFL Alice unit's role in shaping machine learning and AI in Europe, focusing on research advancements and collaboration within the AI community.