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    ML4Jets2021
    ML4Jets2021

    Jul 6 – 8, 2021
    Europe/Zurich timezone

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      Details for Ben Nachman

      Lawrence Berkeley National Lab. (US)

      Author in the following contributions

      • Calorimeter Simulation Challenge Proposal
      • Symmetry Discovery with Deep Learning
      • Testing Universality in various Monte Carlo Generators in Deep Learning with Application in Higgs-boson pair searches in 2HDM
      • Amplifying Statistics with Generative Models
      • Uncertainty Aware Learning for High Energy Physics
      • OnlineFlow: Trigger Free Analysis Using Online Learned Generative Models
      • Learning Uncertainties the Frequentist Way: Calibration and Correlation in High Energy Physics
      • Latent Space Refinement for Deep Generative Models
      • Identifying the Quantum Properties of Hadronic Resonances using Machine Learning
      • Jet-based TMD measurements with H1 data, unfolded using machine-learning techniques
      • Generative Adversarial Networks for Anomaly Detection at the LHC
      • CATHODE part 2: robustness and comparison to other methods
      • CATHODE part 1: introducing a new model-agnostic search strategy for resonant new physics at the LHC
      • High-dimensional Anomaly Detection with Radiative Return in e+e- Collisions
      CERN
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