Topic: Computer Vision

New CASC research puts sparse autoencoders and concept bottlenecks to work on foundation models.

LLNL researchers have posters and workshop papers accepted to the IEEE/CVF Conference on Computer Vision and Pattern Recognition on June 3–7.

New research reveals subtleties in the performance of neural image compression methods, offering insights toward improving these models for real-world applications.

Highlights include MFEM community workshops, compiler co-design, HPC standards committees, and AI/ML for national security.