KilonovaNet: Surrogate Models of Kilonova Spectra with Conditional Variational Autoencoders

Posted by klaurent Chicago

Kavli Affiliate: Brian Nord | First 5 Authors: Kamilė Lukošiūtė, Geert Raaijmakers, Zoheyr Doctor, Marcelle Soares-Santos, Brian Nord | Summary: Detailed radiative transfer simulations of kilonova spectra play an essential role in multimessenger astrophysics. Using the simulation results in parameter inference studies requires building a surrogate model from the simulation outputs to use in algorithms […]


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i-Razor: A Neural Input Razor for Feature Selection and Dimension Search in Large-Scale Recommender Systems

Posted by klaurent Peking

Kavli Affiliate: Ke Wang | First 5 Authors: Yao Yao, Bin Liu, Haoxun He, Dakui Sheng, Ke Wang | Summary: Input features play a crucial role in the predictive performance of DNN-based industrial recommender systems with thousands of categorical and continuous fields from users, items, contexts, and their interactions. Noisy features and inappropriate embedding dimension […]


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An End-to-end Supervised Domain Adaptation Framework for Cross-Domain Change Detection

Posted by klaurent Tokyo

Kavli Affiliate: Jia Liu | First 5 Authors: Jia Liu, Wenjie Xuan, Yuhang Gan, Juhua Liu, Bo Du | Summary: Existing deep learning-based change detection methods try to elaborately design complicated neural networks with powerful feature representations, but ignore the universal domain shift induced by time-varying land cover changes, including luminance fluctuations and season changes […]


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Dynamic scaling properties of multistep polarization response in ferroelectrics

Posted by klaurent Peking

Kavli Affiliate: Ke Wang | First 5 Authors: Yuri A. Genenko, Sergey Zhukov, Maohua Zhang, Ke Wang, Jurij Koruza | Summary: Ferroelectrics are multifunctional smart materials finding applications in sensor technology, micromechanical actuation, digital information storage etc. Their most fundamental property is the ability of polarization switching under applied electric field. In particular, understanding of […]


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Data Sampling Affects the Complexity of Online SGD over Dependent Data

Posted by klaurent UCAS

Kavli Affiliate: Yi Zhou | First 5 Authors: Shaocong Ma, Ziyi Chen, Yi Zhou, Kaiyi Ji, Yingbin Liang | Summary: Conventional machine learning applications typically assume that data samples are independently and identically distributed (i.i.d.). However, practical scenarios often involve a data-generating process that produces highly dependent data samples, which are known to heavily bias […]


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Large-gap insulating dimer ground state in monolayer IrTe2

Posted by klaurent Berkeley

Kavli Affiliate: Michael F. Crommie | First 5 Authors: Jinwoong Hwang, Kyoo Kim, Canxun Zhang, Tiancong Zhu, Charlotte Herbig | Summary: Monolayers of two-dimensional van der Waals materials exhibit novel electronic phases distinct from their bulk due to the symmetry breaking and reduced screening in the absence of the interlayer coupling. In this work, we […]


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A partnership of the lipid scramblase XK and of the lipid transfer protein VPS13A at the plasma membrane

Posted by klaurent Yale

Kavli Affiliate: Pietro DeCamilli | Authors: Andrés Guillén Samander, Yumei Wu, S. Sebastian Pineda, Francisco J. García, Julia N. Eisen, Marianna Leonzino, Berrak Uğur, Manolis Kellis, Myriam Heiman and Pietro De Camilli | Summary: Chorea-acanthocytosis and McLeod syndrome are diseases with shared clinical manifestations caused by mutations in VPS13A and XK, respectively. Key features of […]


Continue.. A partnership of the lipid scramblase XK and of the lipid transfer protein VPS13A at the plasma membrane

Knowledge-Spreader: Learning Facial Action Unit Dynamics with Extremely Limited Labels

Posted by klaurent Berkeley

Kavli Affiliate: Xiang Zhang | First 5 Authors: Xiaotian Li, Xiang Zhang, Taoyue Wang, Lijun Yin, | Summary: Recent studies on the automatic detection of facial action unit (AU) have extensively relied on large-sized annotations. However, manually AU labeling is difficult, time-consuming, and costly. Most existing semi-supervised works ignore the informative cues from the temporal […]


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