Related papers: Determination of the CMSSM Parameters using Neural…
We consider machine learning techniques associated with the application of a Boosted Decision Tree (BDT) to searches at the Large Hadron Collider (LHC) for pair-produced lepton partners which decay to leptons and invisible particles. This…
Linear mixed models (LMMs) are used as an important tool in the data analysis of repeated measures and longitudinal studies. The most common form of LMMs utilize a normal distribution to model the random effects. Such assumptions can often…
Thousands of person-years have been invested in searches for New Physics (NP), the majority of them motivated by theoretical considerations. Yet, no evidence of beyond the Standard Model (BSM) physics has been found. This suggests that…
Meta-learning consists in learning learning algorithms. We use a Long Short Term Memory (LSTM) based network to learn to compute on-line updates of the parameters of another neural network. These parameters are stored in the cell state of…
Blind inverse problems arise in many experimental settings where both the signal of interest and the forward operator are (partially) unknown. In this context, methods developed for the non-blind case cannot be adapted in a straightforward…
We propose to use deep learning to estimate parameters in statistical models when standard likelihood estimation methods are computationally infeasible. We show how to estimate parameters from max-stable processes, where inference is…
Few-shot learning in remote sensing remains challenging due to three factors: the scarcity of labeled data, substantial domain shifts, and the multi-scale nature of geospatial objects. To address these issues, we introduce Adaptive…
We update previous frequentist analyses of the CMSSM and NUHM1 parameter spaces to include the public results of searches for supersymmetric signals using ~1 /fb of LHC data recorded by ATLAS and CMS and ~0.3/fb of data recorded by LHCb in…
We discuss the prospects for detecting supersymmetric particles in variants of the minimal supersymmetric extension of the Standard Model (MSSM), in light of laboratory and cosmological constraints. We first assume that the lightest…
Search for supersymmetry is carried out in the framework of the Minimal Supersymmetric Standard Model (MSSM). Using the software programs SOFTSUSY and PROSPINO, the mass spectrum and the production cross-sections of superpartners are…
Different search strategies for supersymmetry have been employed by the LHC general-purpose experiments using early data. As proven by their early results, these strategies are promising, but raise the question of how well they will…
We investigate the parameter space of a model which extends next to minimal supersymmetric standard model (NMSSM) with the vectorlike (VL) particles. We find that the $10+\overline{10}$ model can explain the possible diphoton excess…
We explore unique considerations involved in fitting ML models to data with very high precision, as is often required for science applications. We empirically compare various function approximation methods and study how they scale with…
We propose a rigorous and effective way to compare experimental and theoretical histograms, incorporating the different sources of statistical and systematic uncertainties. This is a useful tool to extract as much information as possible…
The LHC inverse problem refers to the difficulties in determining the parameters of an underlying theory from data (to be) taken by the LHC experiments: if they find signals of new physics, and an underlying theory is assumed, could its…
Understanding the source of the universe's asymmetry between matter and antimatter is one of the major open questions in particle physics. In this work, the sensitivity of novel machine-learning-based inference techniques to CP-odd and…
The precision of Cosmic Microwave Background (CMB) experiments, specifically its lensing reconstruction, has reached the limit where non-linear corrections cannot be ignored. Neglecting these corrections results in biased constraints on…
We present a further development of a method for accelerating the calculation of CMB power spectra, matter power spectra and likelihood functions for use in cosmological Bayesian inference. The algorithm, called {\sc CosmoNet}, is based on…
We review the status of the phenomenology of light neutralinos in an effective Minimal Supersymmetric extension of the Standard Model (MSSM) at the electroweak scale, in light of new results obtained at the CERN Large Hadron Collider. First…
We review the result of SUSY parameter fits based on frequentist analyses of experimental constraints from electroweak precision data, (g-2)_mu, B-physics and cosmological data. We investigate the parameters of the constrained MSSM (CMSSM)…