The free energy of twisting spins in Mn$_3$Sn

Kavli Affiliate: Leon Balents | First 5 Authors: Xiaokang Li, Shan Jiang, Qingkai Meng, Huakun Zuo, Zengwei Zhu | Summary: The magnetic free energy is usually quadratic in magnetic field and depends on the mutual orientation of the magnetic field and the crystalline axes. Tiny in magnitude, this magnetocrystalline anisotropy energy (MAE) is nevertheless indispensable […]


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Geometric rigidity and anomalous elasticity of cellular tissue vertex model

Kavli Affiliate: Mark J. Bowick | First 5 Authors: Arthur Hernandez, Michael F. Staddon, Mark J. Bowick, M. Cristina Marchetti, Michael Moshe | Summary: Vertex Models, as used to describe cellular tissue, have an energy controlled by deviations from both a target area and a target perimeter. The constrained nonlinear relation between area and perimeter, […]


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Anomalous elasticity of cellular tissue vertex model

Kavli Affiliate: Mark J. Bowick | First 5 Authors: Arthur Hernandez, Michael F. Staddon, Mark J. Bowick, M. Cristina Marchetti, Michael Moshe | Summary: Vertex Models, as used to describe cellular tissue, have an energy controlled by deviations of each cell area and perimeter from target values. The constrained nonlinear relation between area and perimeter […]


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Assisted Learning for Organizations with Limited Data

Kavli Affiliate: Yi Zhou | First 5 Authors: Cheng Chen, Jiaying Zhou, Jie Ding, Yi Zhou, | Summary: We develop an assisted learning framework for assisting organization-level learners to improve their learning performance with limited and imbalanced data. In particular, learners at the organization level usually have sufficient computation resource, but are subject to stringent […]


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Assisted Learning for Organizations with Limited Imbalanced Data

Kavli Affiliate: Yi Zhou | First 5 Authors: Cheng Chen, Jiaying Zhou, Jie Ding, Yi Zhou, | Summary: In the era of big data, many big organizations are integrating machine learning into their work pipelines to facilitate data analysis. However, the performance of their trained models is often restricted by limited and imbalanced data available […]


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Video Pose Distillation for Few-Shot, Fine-Grained Sports Action Recognition

Kavli Affiliate: Matthew Fisher | First 5 Authors: James Hong, Matthew Fisher, MichaĆ«l Gharbi, Kayvon Fatahalian, | Summary: Human pose is a useful feature for fine-grained sports action understanding. However, pose estimators are often unreliable when run on sports video due to domain shift and factors such as motion blur and occlusions. This leads to […]


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Subregion Spectrum Form Factor via Pseudo Entropy

Kavli Affiliate: Masahiro Nozaki | First 5 Authors: Kanato Goto, Masahiro Nozaki, Kotaro Tamaoka, , | Summary: We introduce a subsystem generalization of the spectral form factor via pseudo entropy, the von-Neumann entropy for the reduced transition matrix. We consider a transition matrix between the thermofield double state and its time-evolved state in two-dimensional conformal […]


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Robust decoding in monitored dynamics of open quantum systems with Z_2 symmetry

Kavli Affiliate: Matthew P. A. Fisher | First 5 Authors: Yaodong Li, Matthew P. A. Fisher, , , | Summary: We explore a class of "open" quantum circuit models with local decoherence ("noise") and local projective measurements, each respecting a global Z_2 symmetry. The model supports a spin glass phase where the Z_2 symmetry is […]


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Decodable hybrid dynamics of open quantum systems with Z_2 symmetry

Kavli Affiliate: Matthew P. A. Fisher | First 5 Authors: Yaodong Li, Matthew P. A. Fisher, , , | Summary: We explore a class of "open" quantum circuit models with local decoherence ("noise") and local projective measurements, each respecting a global Z_2 symmetry. The model supports a spin glass phase where the Z_2 symmetry is […]


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GLASS: Geometric Latent Augmentation for Shape Spaces

Kavli Affiliate: Matthew Fisher | First 5 Authors: Sanjeev Muralikrishnan, Siddhartha Chaudhuri, Noam Aigerman, Vladimir Kim, Matthew Fisher | Summary: We investigate the problem of training generative models on a very sparse collection of 3D models. We use geometrically motivated energies to augment and thus boost a sparse collection of example (training) models. We analyze […]


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