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- University of MichiganUS160 papers
- Joint Institute for Nuclear ResearchRU96 papers
- Michigan State UniversityUS93 papers
- Fermi National Accelerator LaboratoryUS88 papers
- University of ManchesterGB87 papers
- Iowa State UniversityUS81 papers
- Seattle UniversityUS79 papers
- University of WashingtonUS79 papers
- Czech Academy of SciencesCZ78 papers
- Indiana University BloomingtonUS77 papers
- Lomonosov Moscow State UniversityRU77 papers
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168 papers
Inchworm tensor train hybridization expansion quantum impurity solver
Yang Yu, André Erpenbeck, Dominika Zgid +3
The investigation of quantum impurity models plays a crucial role in condensed matter physics because of their wide-ranging applications, such as embedding theories and transport p…
Preconditioned Gradient Descent for Over-Parameterized Nonconvex Matrix Factorization
Gavin Zhang, Salar Fattahi, Richard Y. Zhang
In practical instances of nonconvex matrix factorization, the rank of the true solution is often unknown, so the rank of the model can be overspecified as $r>r^{\st…
Siamese Learning-based Monarch Butterfly Localization
Sara Shoouri, Mingyu Yang, Gordy Carichner +7
A new GPS-less, daily localization method is proposed with deep learning sensor fusion that uses daylight intensity and temperature sensor data for Monarch butterfly tracking. Prio…
A Venus in the Making? Predictions for JWST Observations of the Ultracool M-Dwarf planet LP 890-9 c
Jonathan Gomez Barrientos, Lisa Kaltenegger, Ryan J. MacDonald
The recently discovered transiting super-Earth LP 890-9 c is potentially one of the best rocky exoplanets for atmospheric characterization. Orbiting an ultracool M-dwarf at the inn…
Multiplicity of northern bright O-type stars with optical long baseline interferometry
Cyprien Lanthermann, Jean-Baptiste Le Bouquin, Hugues Sana +16
The study of the multiplicity of massive stars gives hints on their formation processes and their evolutionary paths, which are still not fully understood. Large separation binarie…
Environment Generation for Zero-Shot Compositional Reinforcement Learning
Izzeddin Gur, Natasha Jaques, Yingjie Miao +4
Many real-world problems are compositional - solving them requires completing interdependent sub-tasks, either in series or in parallel, that can be represented as a dependency gra…