Robotics is entering a new phase where general-purpose learning matters as much as mechanical design. Instead of programming ...

If you want to improve your aerobic capacity, play full-court basketball, not softball. To improve your analytical skills, learn to play chess or bridge, not Chutes and Ladders. If you really want to ...

Graph out-of-distribution (OOD) generalization remains a major challenge in graph neural networks (GNNs). Invariant learning, aiming to extract invariant features across varied distributions, has ...

I recently ran across a blog post that discusses a very important characteristic for machine learning solutions – Generalization. If you’ve ever wondered about the primary reason why machines can ...

Variability is crucially important for learning new skills. Consider learning how to serve in tennis. Should you always practice serving from the exact same location on the court, aiming at exactly ...

The effect of variability on learning is recognized in many fields: learning is harder when input is variable, but variability leads to better generalization of the knowledge we learned. In this ...

Graph out-of-distribution (OOD) generalization remains a major challenge in graph neural networks (GNNs). Invariant learning, aiming to extract ...