Search Results for author:
Found 4 papers, 3 papers with code
Estimation Beyond Data Reweighting: Kernel Method of Moments
We provide a variant of our estimator for conditional moment restrictions and show that it is asymptotically first-order optimal for such problems.
Functional Generalized Empirical Likelihood Estimation for Conditional Moment Restrictions
Important problems in causal inference, economics, and, more generally, robust machine learning can be expressed as conditional moment restrictions, but estimation becomes challenging as it requires solving a continuum of unconditional moment restrictions.
Learned residual Gerchberg-Saxton network for computer generated holography
Instead of an iterative optimization algorithm that converges to a (sub-)optimal solution, the inverse problem can be solved by training a neural network to directly estimate the inverse operator.
Quantifying the Effects of Contact Tracing, Testing, and Containment Measures in the Presence of Infection Hotspots
Multiple lines of evidence strongly suggest that infection hotspots, where a single individual infects many others, play a key role in the transmission dynamics of COVID-19.
