FSML Lecture Series – Panos Stinis: When big neural networks are not enough: physics, multi-fidelity and kernels
2004 Lay Auto LabWhen big neural networks are not enough: physics, multi-fidelity and kernels
When big neural networks are not enough: physics, multi-fidelity and kernels
Identifying coherent structures and controlling turbulent flows through deep learning
From Turbulent Flows to Video Games: Managing Large-Scale Data with Tensor Decomposition
Flow matching in cell trajectories and protein design
Flow matching in cell trajectories and protein design
Learn about academic opportunities and fellowships for graduate students who combine Scientific Computing with Applied Physics, Astronomy, Biophysics, Chemistry, Earth and Environmental Sciences, Math, Physics, or any other physical science. […]
Learn about academic opportunities and fellowships for graduate students who combine Scientific Computing with Biology, Kinesiology, Medicine, Pharmacy, Public Health, or any other biological or health-related science. This session will […]
Complex Time Representation and Observability of Repeated Measurement Processes with Applications to Spacekime Analytics
"Bridging Wavefunctions and Density Functionals: Unlocking Accurate Data for Functional Development" - Vaibhav Khanna (Chemistry and Scientific Computing)
"Turbulence transport and size segregation of shock-driven multiphase flows" - Archana Sridhar (Aerospace Engineering and Scientific Computing)
"BME and Scientific Computing" - Ashley Tan (Biomedical Engineering and Scientific Computing)
"Emergence of three-dimensional structures from vortex pair instabilities in shocked interfacial flows" - William White (Mechanical Engineering and Scientific Computing)