Welcome to the RAIVN Lab
The Reasoning, AI and VisioN (RAIVN) Lab at Paul G. Allen School of Computer Science and Engineering, University of Washington is directed by Prof. Ali Farhadi. Our research is at the intersection of Computer Vision, Machine Learning, Natural Language Processing and Robotics and is targetted towards helping computers improve their perception and reasoning. RAIVN Lab's famous research break-throughs include YOLO, XNor-Net, VCR, BiDAF among many other amazing projects.
Recent News
- March 2022: Model soups achieve the new current best accuracy on ImageNet.
- November 2021: UW CSE (Allen School) Colloquium video covering some of our recent research!
- October 2021: 2 papers accepted to NeurIPS 2021.
- September 2021: 1 paper accepted to CoRL 2021.
- July 2021: 2 papers accepted to ICCV 2021.
- May 2021: 1 paper accepted to ACL 2021.
- May 2021: 1 paper accepted to ICML 2021.
- March 2021: 2 papers accepted to NAACL 2021.
- February 2021: 2 papers accepted to CVPR 2021.
- January 2021: 3 papers accepted to ICLR 2021. Older News
Sponsors
@RAIVNLab
@RAIVNLabVisit Us
CSE2 230,
Bill & Melinda Gates Center For Computer Science & Engineering,
Paul G. Allen School of Computer Science & Engineering,
University of Washington, Seattle, WA 98195.
Bill & Melinda Gates Center For Computer Science & Engineering,
Paul G. Allen School of Computer Science & Engineering,
University of Washington, Seattle, WA 98195.
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