163 citations · 645 across the 7 of their papers we have counts for
7 papers
Effective LHC measurements with matrix elements and machine learning
Johann Brehmer, Kyle Cranmer, Irina Espejo +3
One major challenge for the legacy measurements at the LHC is that the likelihood function is not tractable when the collected data is high-dimensional and the detector response ha…
Likelihood-free inference with an improved cross-entropy estimator
Markus Stoye, Johann Brehmer, Gilles Louppe +2
We extend recent work (Brehmer, et. al., 2018) that use neural networks as surrogate models for likelihood-free inference. As in the previous work, we exploit the fact that the joi…
Working Memory Networks: Augmenting Memory Networks with a Relational Reasoning Module
Juan Pavez, Héctor Allende, Héctor Allende-Cid
During the last years, there has been a lot of interest in achieving some kind of complex reasoning using deep neural networks. To do that, models like Memory Networks (MemNNs) hav…
Mining gold from implicit models to improve likelihood-free inference
Johann Brehmer, Gilles Louppe, Juan Pavez +1
Simulators often provide the best description of real-world phenomena. However, they also lead to challenging inverse problems because the density they implicitly define is often i…
A Guide to Constraining Effective Field Theories with Machine Learning
Johann Brehmer, Kyle Cranmer, Gilles Louppe +1
We develop, discuss, and compare several inference techniques to constrain theory parameters in collider experiments. By harnessing the latent-space structure of particle physics p…
Constraining Effective Field Theories with Machine Learning
Johann Brehmer, Kyle Cranmer, Gilles Louppe +1
We present powerful new analysis techniques to constrain effective field theories at the LHC. By leveraging the structure of particle physics processes, we extract extra informatio…
Approximating Likelihood Ratios with Calibrated Discriminative Classifiers
Kyle Cranmer, Juan Pavez, Gilles Louppe
In many fields of science, generalized likelihood ratio tests are established tools for statistical inference. At the same time, it has become increasingly common that a simulator…