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thumbnail image for post: Building Scalable Visual Intelligence: From Represention to Understanding and Generation

Building Scalable Visual Intelligence: From Represention to Understanding and Generation

Event Category:
VASC Seminar
Speaker:
Saining Xie
Event Time:
Monday, October 21st - 3:30 PM
thumbnail image for post: Learning to create 3D content

Learning to create 3D content

Event Category:
PhD Thesis Proposal
Speaker:
Kangle Deng
Event Time:
Monday, October 21st - 4:30 PM
thumbnail image for post: Trustworthy Learning using Uncertain Interpretation of Data

Trustworthy Learning using Uncertain Interpretation of Data

Event Category:
PhD Thesis Defense
Speaker:
Jack Henry Good
Event Time:
Wednesday, October 23rd - 3:30 PM

Innovative Framework Drives Autonomous Learning and Task Mastery

Many people learn how to ride a bike at some point in their lives. When children are learning, adults can only guide them to a certain point. A large portion of developing this new skill depends on independent trial and error from the child.  After days of practice, and perhaps a fall or two, ch...

Google CEO Sundar Pichai Launches the 2024-25 President’s Lecture Series at Carnegie Mellon

On Wednesday, Sept. 18, Google and Alphabet CEO Sundar Pichai traveled to Carnegie Mellon University to tour research labs, talk with faculty and students about emerging technologies and officially kick off the first President’s Lecture Series event of the new academic year. Pichai’s whirlwin...
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Building Scalable Visual Intelligence: From Represention to Understanding and Generation

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Home2024-03-19T11:25:29-04:00

Upcoming

October
21
Mon
VASC Seminar
Saining Xie
Courant Institute of Mathematical Sciences, New York University
Building Scalable Visual Intelligence: From Represention to Understanding and Generation
October
21
Mon
PhD Thesis Proposal
Kangle Deng
Robotics Institute,
Carnegie Mellon University
Learning to create 3D content
October
23
Wed
PhD Thesis Defense
Jack Henry Good
Robotics Institute,
Carnegie Mellon University
Trustworthy Learning using Uncertain Interpretation of Data
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