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14:30
Relativity Wasn’t in the Training Set
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Miles Cranmer
(University of Cambridge)
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14:50
Symbolic Regression
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Douglas Adams
(University of Virginia)
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15:10
Neural Net ensembles for Bayesian inference of PDFs
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Maria Ubiali
(University of Cambridge)
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15:45
Artificial Intelligence in the EIC era at the BSM-PDF frontier
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Tim Hobbs
(Argonne National Laboratory)
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16:05
ML-accelerated sampling for theory
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Phiala Shanahan
(MIT)
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16:25
Generative AI for data analysis and preservation
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Marco Battaglieri
(Jefferson Lab)
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16:45
What we talk about when we talk about gluon saturation
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Peter Jacobs
(Lawrence Berkeley National Laboratory)
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17:20
DeepSub: Deep Image Reconstruction for Background Subtraction in Heavy-Ion Collisions
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Umar Sohail Qureshi
(Stanford University)
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17:30
Deep Neural Networks for Extracting the 3D Structure of Nucleon at the EIC
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Ishara Fernando
(University of Virginia)
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17:40
Extraction of Chiral Odd Compton form factors using Maximum Likelihood Method from Exclusive 𝛑0 production experiment.
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Saraswati Pandey
(member@virginia.edu;staff@virginia.edu;employee@virginia.edu)
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17:50
Neural Network Generalized Parton Distributions
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Zaki Panjsheeri
(member@virginia.edu;student@virginia.edu;alum@virginia.edu;employee@virginia.edu;staff@virginia.edu)
