Stanford Seminar - Representation Learning for Autonomous Robots, Anima Anandkumar

Stanford University via YouTube

YouTube

60 Courses


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Overview

Explore the frontier of technology with Stanford University's seminar on "Representation Learning for Autonomous Robots" presented by Anima Anandkumar. In the realm of autonomous robotics, the quest for efficiency, agility, and versatility is paramount. These machines must adapt to a plethora of tasks and environmental challenges, necessitating the development of sophisticated representations of their domain and tasks. This is achieved through leveraging diverse data sources, including demonstrations and simulations, to foster learning that is both generalizable and robust.

Anima Anandkumar will delve into the critical components required to cultivate these capabilities, highlighting the importance of robust self-supervised learning, the integration of uncertainty awareness, and the principle of compositionality. Utilizing NVIDIA Isaac, this seminar showcases how GPU acceleration can revolutionize robot learning, enabling scalable solutions across varied tasks and domains.

This seminar is part of a series offered by Stanford University, available on YouTube, and falls under the categories of Autonomous Vehicles Courses and Self-supervised Learning Courses. Join us to unravel the complexities and discover the potential of autonomous robots through advanced representation learning.

Syllabus


Taught by

Stanford Online


Tags

united states

provider YouTube

YouTube

34 Courses


YouTube

pricing Free Online Course
language English
duration 56 minutes
sessions On-Demand