LOITS is a differentiable sampling method, demonstrated in a GAN closure test, that maps sampled events back to the parameters of a target density for event-level inference.
xθ = LI(u;X k, Yk(θ)).(13) Here,X k, Yk(θ) represent the subgrid and corre- sponding local CDF values
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
hep-ph 1years
2025 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
Toward an event-level analysis of hadron structure using differential programming
LOITS is a differentiable sampling method, demonstrated in a GAN closure test, that maps sampled events back to the parameters of a target density for event-level inference.