Colloquium

We revisit the “One Learning Algorithm Hypothesis” of Andrew Ng (Google Brain) according to which the brain of higher-level animals and of humans processes and perceives sensory data (vision, sound, […]

Minimally invasive and chronic physiological monitoring can provide an effective means of disease prevention and early detection while the cumulative big data can unveil hidden patterns in our physiology. Yet, […]

Geometric perception is the task of estimating geometric models (e.g., object pose and 3D structure) from sensor measurements and priors (e.g., point clouds and neural network detections). Geometric perception is […]

Deep networks often achieve better accuracy as we employ larger models. However, modern machine learning applications involve multiple considerations alongside accuracy, such as resource-efficiency, robustness, or fairness. Deploying ML in […]

Rapid progress in quantum computing technologies is ushering in a new era for quantum many-body physics. Today's noisy, intermediate-scale quantum (NISQ) devices, while still far from fault-tolerant quantum computers, are […]

Feedback-driven decision-making systems are at the emerging frontier of machine learning applications. Upcoming applications of societal consequence, such as self-driving vehicles and smartwatch-based health interventions, have to contend with the […]

From autonomous cars in cities to mobile manipulators at home, robots must interact with people. What makes this hard is that human behavior—especially when interacting with other agents—is vastly complex, […]

Robotics stands as one of the most impactful and promising endeavors of our times. Learning to interact with the world is fundamental for solving some of our most pressing societal […]