Learning Operators - Lecture 3

Explore a 56-minute conference talk by Siddhartha Mishra on learning operators, recorded during the "CEMRACS: Scientific Machine Learning" thematic meeting at the Centre International de Rencontres Mathématiques in Marseille, France. Delve into topics such as numerical experiments, generalization, comparison with numerical methods, error distribution, and resolution dependence. Examine applications in Allen Khan equations, two-dimensional advection, and downstream tasks. Investigate interpretability, inverse problems in optical and seismic imaging, neural inverse operators, and continuous-discrete equivalence. Gain insights into architecture and the Helmholtz equation. Access this video and other mathematical talks on CIRM's Audiovisual Mathematics Library, featuring chapter markers, keywords, abstracts, bibliographies, and multi-criteria search functionality.

Introduction
Numerical Experiments
Generalization
Comparison with numerical methods
Inputs and outputs
Error distribution
Personal equation
Resolution dependence
Allen Khan
Two dimensional advection
Other approaches
Downstream tasks
Interpretability
Interpretation
Inverse problems
Optical Imaging
seismic Imaging
Observation Operator
Neural inverse operators
Continuous discrete equivalence
Architecture
Helmholz