Events

Algorithms are increasingly tasked with forecasting the probabilities of uncertain events: a creditor repaying a loan, a user clicking an advertisement, or a word appearing next in a stream of text, for example. Such forecasts are trustworthy if their users can be sure they won't regret treating the predicted probabilities as if they were actual […]

Generative spatial AI offers unprecedented capabilities for photorealistic scene representation, generation, and novel-view synthesis, among other tasks. In this talk, we discuss recent advances in large-scale 3D scene representations, efficient neural rendering approaches, and generative AI strategies that allow us to generate photorealistic multi-view-consistent digital humans and general 3D scenes.

We have recently demonstrated the possibility of learning controllers that are zero-shot transferable to groups of real quadrotors via large-scale, multi-agent, end-to-end reinforcement learning. We train policies parameterized by neural networks that can control individual drones in a group in a fully decentralized manner. Our policies, trained in simulated environments with realistic quadrotor physics, demonstrate […]