Lead author of temporal straightening paper proposing curvature regularization to improve representation learning for latent planning.
How media typically covers Ying Wang
Ying Wang as author
KernelEvolve, an agentic framework for automated kernel generation and optimization, reduces recommendation model optimization development time from weeks to hours while achieving 100% correctness across 250 benchmark problems on heterogeneous AI accelerators.
“Author of "KernelEvolve: Scaling Agentic Kernel Coding for Heterogeneous AI Accelerators at" on arXiv”
Referenced in coverage
“Lead author of temporal straightening paper proposing curvature regularization to improve representation learning for latent planning.”