Machine learning and AI
ORAL · M11 · ID: 1367805
Presentations
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SYMBA: Symbolic Computation of Amplitudes in High-Energy Physics with Machine Learning
ORAL
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Publication: Preprint at: Arxiv: arXiv:2206.08901<br>Submitted to: Machine Learning: Science and Technology
Presenters
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Abdulhakim Alnuqaydan
University of Kentucky
Authors
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Abdulhakim Alnuqaydan
University of Kentucky
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Simulating 2+1D Lattice Quantum Electrodynamics at Finite Density with Neural Flow Wavefunctions
ORAL
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Publication: https://arxiv.org/pdf/2212.06835.pdf
Presenters
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Di Luo
Massachusetts Institute of Technology
Authors
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Di Luo
Massachusetts Institute of Technology
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Zhuo Chen
Massachusetts Institute of Technology
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Kaiwen Hu
University of Mchigan
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Bryan K Clark
University of Illinois at Urbana-Champaign
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Gauge Equivariant Neural Networks for 2+1D U(1) Gauge Theory Simulations in Hamiltonian Formulation
ORAL
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Publication: arXiv: 2211.03198
Presenters
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Shunyue Yuan
Caltech
Authors
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Shunyue Yuan
Caltech
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Di Luo
Massachusetts Institute of Technology
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James Stokes
University of Michigan, Ann Arbor
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Bryan K Clark
University of Illinois at Urbana-Champaign
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Unbinned and Profiled Unfolding
ORAL
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Presenters
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Jay Chan
University of Wisconsin - Madison
Authors
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Jay Chan
University of Wisconsin - Madison
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Benjamin Nachman
Lawrence Berkeley National Laboratory
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GA Ansatz Optimization on a QAE for HEP Anomaly Detection
ORAL
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Presenters
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Thomas Sievert
Caltech
Authors
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Thomas Sievert
Caltech
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Moment Pooling: Gaining Performance and Interpretability Through Physics Inspired Product Structures
ORAL
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Publication: Associated paper expected in Spring 2023 (No reference)
Presenters
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Rikab Gambhir
Massachusetts Institute of Technology
Authors
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Rikab Gambhir
Massachusetts Institute of Technology
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Jesse D Thaler
Massachusetts Institute of Technology MIT
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Athis Osathapan
Bowdoin College
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Convolutional Visual Networks for Secondary Vertexing in NOvA
ORAL
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Presenters
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Erin Ewart
Indiana University Bloomington
Authors
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Erin Ewart
Indiana University Bloomington
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Diffusion-Based Generative Modeling for LArTPC Images
ORAL
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Presenters
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Zeviel Imani
Tufts University
Authors
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Zeviel Imani
Tufts University
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