| Deep learning in color: towards automated quark/gluon jet discrimination PT Komiske, EM Metodiev, MD Schwartz Journal of High Energy Physics 2017 (1), 1-23, 2017 | 341 | 2017 |
| Energy flow networks: deep sets for particle jets PT Komiske, EM Metodiev, J Thaler Journal of High Energy Physics 2019 (1), 1-46, 2019 | 317 | 2019 |
| The machine learning landscape of top taggers G Kasieczka, T Plehn, A Butter, K Cranmer, D Debnath, BM Dillon, ... SciPost Physics 7 (1), 014, 2019 | 228 | 2019 |
| Energy flow polynomials: A complete linear basis for jet substructure PT Komiske, EM Metodiev, J Thaler Journal of High Energy Physics 2018 (4), 1-54, 2018 | 184 | 2018 |
| The LHC Olympics 2020 a community challenge for anomaly detection in high energy physics G Kasieczka, B Nachman, D Shih, O Amram, A Andreassen, ... Reports on progress in physics 84 (12), 124201, 2021 | 155 | 2021 |
| Metric space of collider events PT Komiske, EM Metodiev, J Thaler Physical review letters 123 (4), 041801, 2019 | 142 | 2019 |
| OmniFold: a method to simultaneously unfold all observables A Andreassen, PT Komiske, EM Metodiev, B Nachman, J Thaler Physical review letters 124 (18), 182001, 2020 | 132 | 2020 |
| Pileup mitigation with machine learning (PUMML) PT Komiske, EM Metodiev, B Nachman, MD Schwartz Journal of High Energy Physics 2017 (12), 1-20, 2017 | 117 | 2017 |
| Learning to classify from impure samples with high-dimensional data PT Komiske, EM Metodiev, B Nachman, MD Schwartz Physical Review D 98 (1), 011502, 2018 | 95 | 2018 |
| An operational definition of quark and gluon jets PT Komiske, EM Metodiev, J Thaler Journal of High Energy Physics 2018 (11), 1-36, 2018 | 81 | 2018 |
| The hidden geometry of particle collisions PT Komiske, EM Metodiev, J Thaler Journal of High Energy Physics 2020 (7), 1-53, 2020 | 55 | 2020 |
| Analyzing -Point Energy Correlators inside Jets with CMS Open Data PT Komiske, I Moult, J Thaler, HX Zhu Physical Review Letters 130 (5), 051901, 2023 | 52 | 2023 |
| Exploring the space of jets with CMS open data PT Komiske, R Mastandrea, EM Metodiev, P Naik, J Thaler Physical Review D 101 (3), 034009, 2020 | 50 | 2020 |
| Cutting multiparticle correlators down to size PT Komiske, EM Metodiev, J Thaler Physical Review D 101 (3), 036019, 2020 | 23 | 2020 |
| Disentangling quarks and gluons in CMS open data PT Komiske, S Kryhin, J Thaler Physical Review D 106 (9), 094021, 2022 | 18 | 2022 |
| Learning to classify from impure samples PT Komiske, EM Metodiev, B Nachman, MD Schwartz arXiv preprint arXiv:1801.10158, 2018 | 16 | 2018 |
| Scaffolding simulations with deep learning for high-dimensional deconvolution A Andreassen, PT Komiske, EM Metodiev, B Nachman, A Suresh, ... arXiv preprint arXiv:2105.04448, 2021 | 15 | 2021 |
| Preserving new physics while simultaneously unfolding all observables P Komiske, WP McCormack, B Nachman Physical Review D 104 (7), 076027, 2021 | 9 | 2021 |
| Learning to remove Pileup at the LHC with Jet Images PT Komiske, EM Metodiev, B Nachman, MD Schwartz Journal of Physics: Conference Series 1085 (4), 042010, 2018 | 7 | 2018 |
| Pileup and Infrared Radiation Annihilation (PIRANHA): a paradigm for continuous jet grooming S Alipour-Fard, PT Komiske, EM Metodiev, J Thaler Journal of High Energy Physics 2023 (9), 1-81, 2023 | 3 | 2023 |
Eric M. MetodievMassachusetts Institute of TechnologyVerified email at mit.edu
