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1. Full Text Energy flow networks: deep sets for particle jets
by Komiske, Patrick T and Metodiev, Eric M and Thaler, Jesse and Massachusetts Inst. of Technology (MIT), Cambridge, MA (United States)
The journal of high energy physics, ISSN 1126-6708, 1/2019, Volume 2019, Issue 1, pp. 1 - 46
QCD Phenomenology | Jets | Quantum Physics | Quantum Field Theories, String Theory | Classical and Quantum Gravitation, Relativity Theory | Physics | Elementary Particles, Quantum Field Theory | Physical Sciences | Physics, Particles & Fields | Science & Technology | Networks | Energy flow | Large Hadron Collider | Flavor (particle physics) | Particle physics | Machine learning | Dependence | Representations | Artificial intelligence | Three dimensional models | PHYSICS OF ELEMENTARY PARTICLES AND FIELDS | CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSICS
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2. Full Text Jet Topics: Disentangling Quarks and Gluons at Colliders
by Metodiev, Eric M and Thaler, Jesse and Massachusetts Inst. of Technology (MIT), Cambridge, MA (United States)
Physical review letters, ISSN 0031-9007, 06/2018, Volume 120, Issue 24, pp. 241602 - 241602
Physics, Multidisciplinary | Physical Sciences | Physics | Science & Technology | Jets | First principles | Quarks | Large Hadron Collider | Gluons | Computer simulation | Phenomenology | Statistics - Machine Learning | High Energy Physics - Phenomenology | High Energy Physics | Astrophysics | Experiment | High Energy Physics - Experiment | High Energy Astrophysical Phenomena | PHYSICS OF ELEMENTARY PARTICLES AND FIELDS
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3. Full Text Energy flow polynomials: a complete linear basis for jet substructure
by Komiske, Patrick T and Metodiev, Eric M and Thaler, Jesse and Massachusetts Inst. of Technology (MIT), Cambridge, MA (United States)
The journal of high energy physics, ISSN 1126-6708, 4/2018, Volume 2018, Issue 4, pp. 1 - 54
QCD Phenomenology | Jets | Quantum Physics | Quantum Field Theories, String Theory | Classical and Quantum Gravitation, Relativity Theory | Physics | Elementary Particles, Quantum Field Theory | Physical Sciences | Physics, Particles & Fields | Science & Technology | Algorithms | Energy flow | Energy consumption | Energy | Correlators | Graph theory | Polynomials | Graphical representations | Marking | PHYSICS OF ELEMENTARY PARTICLES AND FIELDS
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4. Full Text Classification without labels: learning from mixed samples in high energy physics
by Metodiev, Eric M and Nachman, Benjamin and Thaler, Jesse and Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
The journal of high energy physics, ISSN 1126-6708, 10/2017, Volume 2017, Issue 10, pp. 1 - 18
Jets | Quantum Physics | Quantum Field Theories, String Theory | Classical and Quantum Gravitation, Relativity Theory | Physics | Elementary Particles, Quantum Field Theory | Physical Sciences | Physics, Particles & Fields | Science & Technology | Quarks | Collisions (Nuclear physics) | Analysis | Machine learning | Statistics - Machine Learning | High Energy Physics - Phenomenology | High Energy Physics | Experiment | Nuclear and particle physics. Atomic energy. Radioactivity | Nuclear & Particles Physics | High Energy Physics - Experiment | Mathematical Sciences | PHYSICS OF ELEMENTARY PARTICLES AND FIELDS
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5. Full Text Pileup Mitigation with Machine Learning (PUMML)
by Komiske, Patrick T and Metodiev, Eric M and Nachman, Benjamin and Schwartz, Matthew D and Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
The journal of high energy physics, ISSN 1126-6708, 12/2017, Volume 2017, Issue 12, pp. 1 - 20
Jets | Quantum Physics | Quantum Field Theories, String Theory | Classical and Quantum Gravitation, Relativity Theory | Physics | Elementary Particles, Quantum Field Theory | Physical Sciences | Physics, Particles & Fields | Science & Technology | Algorithms | Neural networks | Traffic accidents | Machine learning | Radiation | Energy distribution | Artificial neural networks | Ions | Charged particles | Neutral particles | Artificial intelligence | Contamination | Statistics - Machine Learning | Astrophysics | Mathematical Physics | Nuclear and particle physics. Atomic energy. Radioactivity | Atomic | High Energy Physics - Experiment | Molecular | Mathematical Sciences | High Energy Astrophysical Phenomena | High Energy Physics - Phenomenology | Nuclear | Nuclear & Particles Physics | Particle and Plasma Physics | PHYSICS OF ELEMENTARY PARTICLES AND FIELDS
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6. Full Text Deep learning in color: towards automated quark/gluon jet discrimination
by Komiske, Patrick T and Metodiev, Eric M and Schwartz, Matthew D and Harvard Univ., Cambridge, MA (United States)
The journal of high energy physics, ISSN 1126-6708, 1/2017, Volume 2017, Issue 1, pp. 1 - 23
Jets | Quantum Physics | Quantum Field Theories, String Theory | Classical and Quantum Gravitation, Relativity Theory | Physics | Elementary Particles, Quantum Field Theory | Physical Sciences | Physics, Particles & Fields | Science & Technology | Automation | Discrimination | Neural networks | Physicists | Mechanization | Quarks | Artificial intelligence | Networks | Computer simulation | Gluons | Transverse momentum | Images | Charged particles | Statistics - Machine Learning | High Energy Physics - Phenomenology | High Energy Physics | Nuclear and High Energy Physics | Experiment | PHYSICS OF ELEMENTARY PARTICLES AND FIELDS
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7. Full Text An operational definition of quark and gluon jets
by Komiske, Patrick T and Metodiev, Eric M and Thaler, Jesse and Massachusetts Inst. of Technology (MIT), Cambridge, MA (United States)
The journal of high energy physics, ISSN 1126-6708, 11/2018, Volume 2018, Issue 11, pp. 1 - 36
Jets | Quantum Physics | Quantum Field Theories, String Theory | Classical and Quantum Gravitation, Relativity Theory | Physics | Elementary Particles, Quantum Field Theory | Physical Sciences | Physics, Particles & Fields | Science & Technology | Analysis | Quarks | Flavor (particle physics) | CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSICS | jets
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8. Full Text A theory of quark vs. gluon discrimination
by Larkoski, Andrew J and Metodiev, Eric M
The journal of high energy physics, ISSN 1029-8479, 10/2019, Volume 2019, Issue 10, pp. 1 - 53
Jets | Quantum Physics | Quantum Field Theories, String Theory | Classical and Quantum Gravitation, Relativity Theory | Physics | Elementary Particles, Quantum Field Theory | Physical Sciences | Physics, Particles & Fields | Science & Technology | Aircraft exhaust emissions | Neural networks | Analysis | Machine learning | Quarks | Distribution (Probability theory) | Collisions (Nuclear physics) | First principles | Likelihood ratio | Body kinematics | Discrimination | Partons | Gluons | Mathematical analysis | Artificial intelligence | Distribution functions
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9. Full Text Exploring the space of jets with CMS open data
by Komiske, Patrick T and Mastandrea, Radha and Metodiev, Eric M and Naik, Preksha and Thaler, Jesse and Massachusetts Inst. of Technology (MIT), Cambridge, MA (United States)
Physical review. D, ISSN 2470-0010, 02/2020, Volume 101, Issue 3
Physical Sciences | Astronomy & Astrophysics | Physics, Particles & Fields | Physics | Science & Technology | Substructures | Protons | Energy flow | Subtraction | Metric space | Large Hadron Collider | Particle collisions | Transverse momentum | Jets | Sensors | Solenoids | Open data | NUCLEAR PHYSICS AND RADIATION PHYSICS | PHYSICS OF ELEMENTARY PARTICLES AND FIELDS
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