11 citations · 25 across the 7 of their papers we have counts for
8 papers · 1 filter
Faithful Uncertainties in ML-Based Inverse Problems: GPs, NNs and NTKs for the Triplet PDF
Nina Elmer, Sven Krippendorf, Maria Ubiali
Machine-learning methods are increasingly used to solve inverse problems in physics, where a faithful estimate of the uncertainty on the reconstructed function is as important as i…
MadNIS at NLO
Giovanni De Crescenzo, Javier Mariño Villadamigo, Nina Elmer +4
We combine fast amplitude surrogates with neural importance sampling to accelerate NLO calculations. For virtual corrections, a learned ratio to the Born matrix element with calibr…
Forecasting Generative Amplification
Henning Bahl, Sascha Diefenbacher, Nina Elmer +2
Generative networks are perfect tools to enhance the speed and precision of LHC simulations. Especially when generating events beyond the size of the training dataset, it is import…
Amplitude Uncertainties Everywhere All at Once
Henning Bahl, Nina Elmer, Tilman Plehn +1
Ultra-fast, precise, and controlled amplitude surrogates are essential for future LHC event generation. First, we investigate the noise reduction and biases of network ensembles an…
Accurate Surrogate Amplitudes with Calibrated Uncertainties
Henning Bahl, Nina Elmer, Luigi Favaro +3
Neural networks for LHC physics have to be accurate, reliable, and controlled. Using neural surrogates for the prediction of loop amplitudes as a use case, we first show how activa…
A Global View of the EDM Landscape
Skyler Degenkolb, Nina Elmer, Tanmoy Modak +2
Permanent electric dipole moments (EDMs) are sensitive probes of the symmetry structure of elementary particles, which in turn is closely tied to the baryon asymmetry in the univer…
Staying on Top of SMEFT-Likelihood Analyses
Nina Elmer, Maeve Madigan, Tilman Plehn +1
We present a new global SMEFT analysis of LHC data in the top sector. After updating our set of measurements, we show how public ATLAS likelihoods can be incorporated into an exter…
To Profile or To Marginalize -- A SMEFT Case Study
Ilaria Brivio, Sebastian Bruggisser, Nina Elmer +3
Global SMEFT analyses have become a key interpretation framework for LHC physics, quantifying how well a large set of kinematic measurements agrees with the Standard Model. This ag…