2 papers
cs.LG2026
It Just Takes Two: Scaling Amortized Inference to Large Sets
Antoine Wehenkel, Michael Kagan, Lukas Heinrich +1
Neural posterior estimation has emerged as a powerful tool for amortized inference, with growing adoption across scientific and applied domains. In many of these applications, the…
hep-ph2025
Variational inference for pile-up removal at hadron colliders with diffusion models
Malte Algren, Tobias Golling, Christopher Pollard +1
In this paper, we present a novel method for pile-up removal of interactions using variational inference with diffusion models, called vipr. Instead of using classification me…