Thursday, March 9, 2023
8:00AM - 8:36AM
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S62.00001: Enhancing Variational Monte Carlo with Neural Network Quantum States
Invited Speaker:
Stefanie Czischek
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Thursday, March 9, 2023
8:36AM - 8:48AM
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S62.00002: Revealing phase diagrams of quantum systems with optimal predictors
Julian Arnold, Frank Schäfer
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Thursday, March 9, 2023
8:48AM - 9:00AM
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S62.00003: Mitigating semiconductor device variability with machine learning
Natalia Ares
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Thursday, March 9, 2023
9:00AM - 9:12AM
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S62.00004: A convolutional hamming distance metric for unsupervised learning of topological order
Gebremedhin A Dagnew, Owen Myers, Chris M Herdman, Lauren E Hayward Sierens
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Thursday, March 9, 2023
9:12AM - 9:24AM
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S62.00005: Machine Learning for Optical Scanning Probe Nanoscopy
Suheng Xu, Xinzhong Chen, Sara Shabani, Yueqi Zhao, Matthew Fu, Andrew Millis, Michael M Fogler, Abhay N Pasupathy, Mengkun Liu, Dmitri N Basov
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Thursday, March 9, 2023
9:24AM - 10:00AM
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S62.00006: Invited Talk: Cristian BonatoBayesian inference for quantum sensing and model learning
Invited Speaker:
Cristian Bonato
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Thursday, March 9, 2023
10:00AM - 10:12AM
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S62.00007: Towards improving generalization of a neural network by interpretation for topological phases of matter
Kacper J Cybinski, Marcin Plodzien, Michal Tomza, Maciej A Lewenstein, Alexandre Dauphin, Anna Dawid
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Thursday, March 9, 2023
10:12AM - 10:24AM
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S62.00008: Learning by confusion: detecting phase transitions from Quantum Monte Carlo data
Owen Bradley, Max Cohen, Richard T Scalettar
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Thursday, March 9, 2023
10:24AM - 10:36AM
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S62.00009: Digital Discovery of a Scientific Concept at the Core of Experimental Quantum Optics
Sören Arlt, Mario Krenn, Carlos Ruiz Gonzalez, Mario Krenn
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Thursday, March 9, 2023
10:36AM - 10:48AM
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S62.00010: From 4D-STEM data to interpretable physics — an unsupervised learning approach to the charge order physics in TaS2
Haining Pan, Krishnanand M Mallayya, James L Hart, Judy J Cha, Eun-Ah Kim
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