scholarly journals Machine learning to alleviate Hubbard-model sign problems

2021 ◽  
Vol 103 (12) ◽  
Author(s):  
Jan-Lukas Wynen ◽  
Evan Berkowitz ◽  
Stefan Krieg ◽  
Thomas Luu ◽  
Johann Ostmeyer
Keyword(s):  
Machine Learning ◽  
Hubbard Model ◽  
Sign Problems

scholarly journals Classifying snapshots of the doped Hubbard model with machine learning

2019 ◽  
Vol 15 (9) ◽  
pp. 921-924 ◽  
Author(s):  
Annabelle Bohrdt ◽  
Christie S. Chiu ◽  
Geoffrey Ji ◽  
Muqing Xu ◽  
Daniel Greif ◽  
...  
Keyword(s):  
Machine Learning ◽  
Hubbard Model

scholarly journals Machine Learning Phase Diagram in the Half-filled One-dimensional Extended Hubbard Model

2019 ◽  
Vol 88 (6) ◽  
pp. 065001 ◽  
Author(s):  
Kazuya Shinjo ◽  
Kakeru Sasaki ◽  
Satoru Hase ◽  
Shigetoshi Sota ◽  
Satoshi Ejima ◽  
...  
Keyword(s):  
Machine Learning ◽  
Phase Diagram ◽  
Hubbard Model ◽  
Learning Phase ◽  
Extended Hubbard Model ◽  
One Dimensional

Mind wandering as data augmentation: How mental travel supports abstraction

2020 ◽  
Vol 43 ◽  
Author(s):  
Myrthe Faber
Keyword(s):  
Machine Learning ◽  
Data Augmentation ◽  
Mental Content ◽  
Mind Wandering ◽  
Theoretical Framework ◽  
Important Addition

Abstract Gilead et al. state that abstraction supports mental travel, and that mental travel critically relies on abstraction. I propose an important addition to this theoretical framework, namely that mental travel might also support abstraction. Specifically, I argue that spontaneous mental travel (mind wandering), much like data augmentation in machine learning, provides variability in mental content and context necessary for abstraction.

Data Mining and Machine Learning

2020 ◽  
Author(s):  
Mohammed J. Zaki ◽  
Wagner Meira, Jr
Keyword(s):  
Machine Learning ◽  
Data Mining
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