LANS Informal Seminar: Anirudh Subramanyam
Anirudh Subramanyam, Postdoctoral Appointee, MCS/ANL
Data-Driven Methods for Robust Optimization Under Uncertainty
Anirudh Subramanyam, Postdoctoral Appointee, MCS/ANL
Data-Driven Methods for Robust Optimization Under Uncertainty
Navjot Kukreja, PhD Student, Imperial College London
Full Waveform Inversion with a Finite Difference DSL
Kevin Carlberg, AI Research Science Manager, Facebook
Nonlinear Model Reduction: Using Machine Learning to Enable Rapid Simulation of Extreme-Scale Physics Models
Rebecca Morrison, Assistant Professor, University of Colorado
Learning Sparse Non-Gaussian Graphical Models
Johannes Brust, Postdoctoral Appointee, MCS/ANL
Limited Memory Structured Quasi-Newton Methods
Elizabeth Qian, PhD Student, MIT
Lift & Learn: A Scientific Machine Learning Framework for Learning Low-Dimensional Models for Nonlinear PDEs
Javad Lavaei, Associate Professor, Department of Industrial Engineering and Operations Research, UC Berkeley
Computational Techniques for Nonlinear Optimization and Learning Problems
Samy Wu Fung, Adjunct Professor, UCLA
A GAN-Based Approach for Solving High-Dimensional Stochastic Mean Field Games
Mike Innes, Software Programmer, Julia Computing
Building Compilers for Numerical Programming
William Moses, PhD Student, MIT
Post-Optimization Automatic Differentiation by Synthesizing LLVM