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| * **Bias and Priors in Machine Learning Calibrations for High Energy Physics**. \\ Rikab Gambhir, Benjamin Nachman, and Jesse Thaler. \\ [[https://doi.org/10.1103/PhysRevD.106.036011|Phys. Rev. D106:036011 (2022)]], [[https://arxiv.org/abs/2205.05084|arXiv:2205.05084]]. | * **Bias and Priors in Machine Learning Calibrations for High Energy Physics**. \\ Rikab Gambhir, Benjamin Nachman, and Jesse Thaler. \\ [[https://doi.org/10.1103/PhysRevD.106.036011|Phys. Rev. D106:036011 (2022)]], [[https://arxiv.org/abs/2205.05084|arXiv:2205.05084]]. | ||
| - | * **Disentangling Quarks and Gluons with CMS Open Data**. \\ Patrick T. Komiske, Serhii Kryhin, and Jesse Thaler. \\ [[https://arxiv.org/abs/2205.04459|arXiv:2205.04459]]. | + | * **Disentangling Quarks and Gluons with CMS Open Data**. \\ Patrick T. Komiske, Serhii Kryhin, and Jesse Thaler. \\ [[https://doi.org/10.1103/PhysRevD.106.056008|Phys Rev D106:056008 (2022)]], [[https://arxiv.org/abs/2205.04459|arXiv:2205.04459]]. |
| * **Learning Uncertainties the Frequentist Way: Calibration and Correlation in High Energy Physics**. \\ Rikab Gambhir, Benjamin Nachman, and Jesse Thaler. \\ [[https://doi.org/10.1103/PhysRevLett.129.082001|Phys. Rev. Lett. 129:082001 (2022)]], [[https://arxiv.org/abs/2205.03413|arXiv:2205.03413]]. | * **Learning Uncertainties the Frequentist Way: Calibration and Correlation in High Energy Physics**. \\ Rikab Gambhir, Benjamin Nachman, and Jesse Thaler. \\ [[https://doi.org/10.1103/PhysRevLett.129.082001|Phys. Rev. Lett. 129:082001 (2022)]], [[https://arxiv.org/abs/2205.03413|arXiv:2205.03413]]. | ||