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20182025
most citedInferring the quantum density matrix with machine learning

15 citations · 38 across the 8 of their papers we have counts for

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stat.ML2025

Quasiprobabilistic Density Ratio Estimation with a Reverse Engineered Classification Loss Function

Matthew Drnevich, Stephen Jiggins, Kyle Cranmer

We consider a generalization of the classifier-based density-ratio estimation task to a quasiprobabilistic setting where probability densities can be negative. The problem with mos…

stat.ML2018★ 1 cited

Backdrop: Stochastic Backpropagation

Siavash Golkar, Kyle Cranmer

We introduce backdrop, a flexible and simple-to-implement method, intuitively described as dropout acting only along the backpropagation pipeline. Backdrop is implemented via one o…