APS March Meeting 2020
Volume 65, Number 1
Monday–Friday, March 2–6, 2020;
Denver, Colorado
Session Index
Session S39: Machine learning for quantum matter IV
Focus
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Sponsoring Units: DCOMP GDS DMP
Chair: Linda Hung, Toyota Research Institute
Room: 703
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S39.00001: Self-learning projective quantum Monte Carlo simulations guided by restricted Boltzmann machines
Invited Speaker:
Estelle Inack
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S39.00002: Self-learning Hybrid Monte Carlo method for first-principles molecular simulations
Yuki Nagai, Masahiko Okumura, Keita Kobayashi, Motoyuki Shiga
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S39.00003: On-the-fly machine learning algorithm for accelerating Monte Carlo sampling: Application to the stochastic analytical continuation
Hongkee Yoon, Myung Joon Han
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S39.00004: Automatic Differentiable Monte Carlo: Theory
Shixin Zhang, Zhou-Quan Wan, Hong Yao
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S39.00005: Automatic Differentiable Monte Carlo: Applications
Zhouquan Wan, Shixin Zhang, Hong Yao
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S39.00006: Optimal Real-Space Renormalization-Group Transformations with Artificial Neural Networks
Jui-Hui Chung, Ying-Jer Kao
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S39.00007: Machine-learning-accelerated predictions of optical properties of condensed systems based on many-body perturbation theory
Sijia Dong, Marco Govoni, Giulia Galli
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S39.00008: Machine Learned Spectral Functions for the Quantum Impurity Problem
Erica Sturm, Matthew R Carbone, Deyu Lu, Andreas Weichselbaum, Robert Konik
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S39.00009: Finding New Mixing Strategies for Self Consistent Field Procedures Using Reinforcement Learning
Daniel Abarbanel, Hong Guo
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S39.00010: Machine learning spin dynamics in the double-exchange systems
Puhan Zhang, Preetha Saha, Gia-Wei Chern
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S39.00011: Machine learning of high-throughput DFT electron densities
Linda Hung, Daniel Schweigert, Arjun Bhargava, Chirranjeevi Gopal
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S39.00012: Machine learning as a solution to the electronic structure problem
Beatriz Gonzalez del Rio, Ramamurthy Ramprasad
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S39.00013: Machine learning spectral indicators of topology
Nina Andrejevic, Jovana Andrejevic, Christopher Rycroft, Mingda Li
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