This event is in the past.It took place on January 15, 2026 at East Hall.


Colloquium: A unifying perspective of scientific machine learning with kernel methods
Burns Park
Dive into kernel methods that bridge equation learning, PDE solvers, and operator learning. Hosseini from UW presents convergence theory and numerical benchmarks for this unifying approach to scientific ML.
Advanced mathematics
Machine learning theory
Academic research talk
Colloquium: A unifying perspective of scientific machine learning with kernel methods
Burns Park


Dive into kernel methods that bridge equation learning, PDE solvers, and operator learning. Hosseini from UW presents convergence theory and numerical benchmarks for this unifying approach to scientific ML.
Advanced mathematics
Machine learning theory
Academic research talk
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