Related papers: SFitter: Reconstructing the MSSM Lagrangian from L…

We present recent results aiming at assessing the coverage properties of Bayesian and frequentist inference methods, as applied to the reconstruction of supersymmetric parameters from simulated LHC data. We discuss the statistical…

Supervised matrix factorization (SMF) is a classical machine learning method that simultaneously seeks feature extraction and classification tasks, which are not necessarily a priori aligned objectives. Our goal is to use SMF to learn…

Robust parameter estimation is a crucial task in several 3D computer vision pipelines such as Structure from Motion (SfM). State-of-the-art algorithms for robust estimation, however, still suffer from difficulties in converging to…

Large neural networks achieve state-of-the-art performance on many tasks, yet their sheer size hinders deployment on resource-constrained devices. Among existing compression approaches, cross-layer parameter sharing remains relatively…

We examine the case of neutralino dark matter in the focus point region of the MSSM, in which the scalar sparticles are too heavy to be produced at the LHC. Whilst it has been previously asserted that the LHC alone would fail to constrain…

Models of weak-scale supersymmetry offer viable dark matter (DM) candidates. Their parameter spaces are however rather large and complex, such that pinning down the actual parameter values from experimental data can depend strongly on the…

Supervised fine-tuning (SFT) is a pivotal approach to adapting large language models (LLMs) for downstream tasks; however, performance often suffers from the ``seesaw phenomenon'', where indiscriminate parameter updates yield progress on…

The parameter space of the phenomenological MSSM (pMSSM) is explored by means of Markov Chain Monte Charlo (MCMC) methods, taking into account the latest LHC results on the Higgs signal at 125 GeV in addition to relevant low-energy…

The quality of numerical reconstructions for unknown parameters in inverse problems depends fundamentally on the selection of experimental data. To ensure a robust reconstruction, it is crucial to select data that are sensitive to the…

The discovery potential for the MSSM with heavy scalars at the LHC in the case of light inos is examined. We discuss the phenomenology of the model and the observables to determine the parameters. We show that for light gauginos, the model…

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…

Theoretical predictions for standard model (SM) processes involving top quarks, such as top quark-antiquark pair or single top production, depend on fundamental SM parameters like the strong coupling constant or the top quark mass. By…

We investigate the model independent nature of the Supersymmetry search strategies at the 7 TeV LHC. To this end, we study the missing-transverse-energy-based searches developed by the ATLAS Collaboration that were essentially designed for…

We identify a benchmark point in the CMSSM's heavy stau-coannihilation region, which is favored by experiments, and demonstrate that it could be accessible to the LHC at $\sqrt{s}=14$ TeV with 300/fb of integrated luminosity via a golden…

We perform a comprehensive exploration of the Constrained MSSM parameters using a Markov Chain Monte Carlo technique and a Bayesian analysis. We compute superpartner masses and other collider observables as well as a cold dark matter…

We introduce Variational State-Space Filters (VSSF), a new method for unsupervised learning, identification, and filtering of latent Markov state space models from raw pixels. We present a theoretically sound framework for latent state…

The 100+ free parameters of the minimal supersymmetric standard model (MSSM) make it computationally difficult to compare systematically with data, motivating the study of specific parameter reductions such as the cMSSM and pMSSM. Here we…

The ATLAS collaboration published supersymmetry limits based on up to about 4.7 \ifb data collected over the year 2011 from LHC runs at 7 TeV. These were mainly interpreted within restricted, particular or simplified models for…

After a quick review of the framework for phenomenological analyses of supersymmetry, we summarize current limits on supersymmetric particle masses and discuss strategies for their searches at the Fermilab Tevatron and the LHC. We also…

We make frequentist analyses of the CMSSM, NUHM1, VCMSSM and mSUGRA parameter spaces taking into account all the public results of searches for supersymmetry using data from the 2010 LHC run and the Xenon100 direct search for dark matter…