APS March Meeting 2020
Volume 65, Number 1
Monday–Friday, March 2–6, 2020;
Denver, Colorado
Session Index
Session M39: Machine Learning for Quantum Matter II
Focus Session
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Show Abstracts |
Sponsoring Units: DCOMP GDS DMP
Chair: Estelle Inack, Perimeter Inst for Theo Phys
Room: 703
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M39.00001: Materials discovery through artificial intelligence
Invited Speaker:
Muratahan Aykol
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M39.00002: Working without data: overcoming gaps in deep learning and physics-based extrapolation
Invited Speaker:
Isaac Tamblyn
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M39.00003: Machine learning models of properties of hybrid 2D materials as potential super lubricants
Marco Fronzi, Mutaz Abu Ghazaleh, Olexandr Isayev, David Winkler, joe shapter, Michael J Ford
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M39.00004: Charge Density Prediction through 3D-CNN for Fast Convergence of Self-Consistent DFT calculation
Iori Kurata, Chikashi Shinagawa, Ryohto Sawada
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M39.00005: Data-driven studies of the magnetic anisotropy of two-dimensional magnetic materials
Yiqi Xie, Trevor David Rhone, Georgios Tritsaris, Oscar Grånäs, Efthimios Kaxiras
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M39.00006: Robust cluster expansion of multicomponent systems using machine learning with structured sparsity
Zhidong Leong, Teck Leong Tan
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M39.00007: Generalizing an Energy Predictor based on Wavelet Scattering for 3D Atomic Systems
Paul Sinz, Michael Swift, Xavier Brumwell, Kwang Jin Kim, Yue Qi, Matthew J Hirn
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M39.00008: Using Machine Learning Models to Predict Higher-Level Quantities from Energy Models
Olivier Malenfant-Thuot, Michel Cote
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M39.00009: AI-guided engineering of nanoscale topological materials
Srilok Srinivasan, Mathew J Cherukara, David Jason Eckstein, Anthony Avarca, Subramanian Sankaranarayanan, Pierre Darancet
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M39.00010: Motif-based machine learning for crystalline materials
Huta Banjade, Shanshan Zhang, Sandro Hauri, Slobodan Vucetic, Qimin Yan
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M39.00011: Machine learning powered kinetic energy functional finding in solid state physics
Hongbin Ren, Xi Dai, Lei Wang
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