Calendar of Events
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RI Seminar
Nima Fazeli
Robotics and Mechanical Engineering, University of Michigan
Sensing the Unseen: Dexterous Tool Manipulation Through Touch and Vision
Abstract: Dexterous tool manipulation is a dance between tool motion, deformation, and force transmission choreographed by the robot's end-effector. Take for example the use of a spatula. How should the robot reason jointly over the tool’s geometry and forces imparted to the environment through vision and touch? In this talk, I will present our recent […]
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VASC Seminar
Kaiming He
Department of Electrical Engineering and Computer Science, MIT-Massachusetts Institute of Technology
Autoregressive Models: Foundations and Open Questions
Abstract: The success of Autoregressive (AR) models in language today is so tremendous that their scope has, in turn, been largely narrowed to specific instantiations. In this talk, we will revisit the foundations of classical AR models, discussing essential concepts that may have been overlooked in modern practice. We will then introduce our recent research […]
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2 events,
Faculty Events
Jun-Yan Zhu
Enabling Collaboration between Creators and Generative Models
Abstract: Generative models have made visual content creation as little effort as writing a short text description. Meanwhile, these models also spark concerns among artists, designers, and photographers about job security and data ownership. This leads to many questions: Will generative models make creators’ jobs obsolete? Should creators stop sharing their work publicly? How can creators […]
RI Seminar
Nikolay Atanasov
Electrical and Computer Engineering, University of California, San Diego
Learning Environment Models for Mobile Robot Autonomy
Abstract: Robots are expected to execute increasingly complex tasks in increasingly complex and a priori unknown environments. A key prerequisite is the ability to understand the geometry and semantics of the environment in real time from sensor observations. This talk will present techniques for learning metric-semantic environment models from RGB and depth observations. Specific examples include […]
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Carnegie Mellon University