SWAT: A System-Wide Approach to Tunable Leakage Mitigation in Encrypted Data Stores

Kavli Affiliate: Hu Zhan | First 5 Authors: Leqian Zheng, Lei Xu, Cong Wang, Sheng Wang, Yuke Hu | Summary: Numerous studies have underscored the significant privacy risks associated with various leakage patterns in encrypted data stores. Most existing systems that conceal leakage either (1) incur substantial overheads, (2) focus on specific subsets of leakage […]


Continue.. SWAT: A System-Wide Approach to Tunable Leakage Mitigation in Encrypted Data Stores

SWAT: A System-Wide Approach to Tunable Leakage Mitigation in Encrypted Data Stores

Kavli Affiliate: Hu Zhan | First 5 Authors: Leqian Zheng, Lei Xu, Cong Wang, Sheng Wang, Yuke Hu | Summary: Numerous studies have underscored the significant privacy risks associated with various leakage patterns in encrypted data stores. While many solutions have been proposed to mitigate these leakages, they either (1) incur substantial overheads, (2) focus […]


Continue.. SWAT: A System-Wide Approach to Tunable Leakage Mitigation in Encrypted Data Stores

Diffuse neutrino background from past core-collapse supernovae

Kavli Affiliate: Shunsaku Horiuchi | First 5 Authors: Shin’ichiro Ando, Nick Ekanger, Shunsaku Horiuchi, Yusuke Koshio, | Summary: Core-collapse supernovae are among the most powerful explosions in the universe, emitting thermal neutrinos that carry away the majority of the gravitational binding energy released. These neutrinos create a diffuse supernova neutrino background (DSNB), one of the […]


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Upgraded waveform model of eccentric binary black hole based on effective-one-body-numerical-relativity for spin-aligned binary black holes

Kavli Affiliate: Lijing Shao | First 5 Authors: Xiaolin Liu, Zhoujian Cao, Lijing Shao, , | Summary: Effective one body numerical relativity waveform models for spin aligned binary black holes (SEOBNR) are based on the effective one body theoretical framework and numerical relativity simulation results. SEOBNR models have evolved through version 1 to version 4. […]


Continue.. Upgraded waveform model of eccentric binary black hole based on effective-one-body-numerical-relativity for spin-aligned binary black holes

An observational upper limit on the rate of gamma-ray bursts with neutron star-black hole merger progenitors

Kavli Affiliate: Salvatore Vitale | First 5 Authors: Sylvia Biscoveanu, Eric Burns, Philippe Landry, Salvatore Vitale, | Summary: Compact-object binary mergers consisting of one neutron star and one black hole (NSBHs) have long been considered promising progenitors for gamma-ray bursts, whose central engine remains poorly understood. Using gravitational-wave constraints on the population-level NSBH mass and […]


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A Transiting Super-Earth in the Radius Valley and An Outer Planet Candidate Around HD 307842

Kavli Affiliate: Avi Shporer | First 5 Authors: Xinyan Hua, Sharon Xuesong Wang, Johanna K. Teske, Tianjun Gan, Avi Shporer | Summary: We report the confirmation of a TESS-discovered transiting super-Earth planet orbiting a mid-G star, HD 307842 (TOI-784). The planet has a period of 2.8 days, and the radial velocity (RV) measurements constrain the […]


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Discovering two-dimensional magnetic topological insulators by machine learning

Kavli Affiliate: Jing Wang | First 5 Authors: Haosheng Xu, Yadong Jiang, Huan Wang, Jing Wang, | Summary: Topological materials with unconventional electronic properties have been investigated intensively for both fundamental and practical interests. Thousands of topological materials have been identified by symmetry-based analysis and ab initio calculations. However, the predicted magnetic topological insulators with […]


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DomainStudio: Fine-Tuning Diffusion Models for Domain-Driven Image Generation using Limited Data

Kavli Affiliate: Jiansheng Chen | First 5 Authors: Jingyuan Zhu, Huimin Ma, Jiansheng Chen, Jian Yuan, | Summary: Denoising diffusion probabilistic models (DDPMs) have been proven capable of synthesizing high-quality images with remarkable diversity when trained on large amounts of data. Typical diffusion models and modern large-scale conditional generative models like text-to-image generative models are […]


Continue.. DomainStudio: Fine-Tuning Diffusion Models for Domain-Driven Image Generation using Limited Data

DomainStudio: Fine-Tuning Diffusion Models for Domain-Driven Image Generation using Limited Data

Kavli Affiliate: Jiansheng Chen | First 5 Authors: Jingyuan Zhu, Huimin Ma, Jiansheng Chen, Jian Yuan, | Summary: Denoising diffusion probabilistic models (DDPMs) have been proven capable of synthesizing high-quality images with remarkable diversity when trained on large amounts of data. Typical diffusion models and modern large-scale conditional generative models like text-to-image generative models are […]


Continue.. DomainStudio: Fine-Tuning Diffusion Models for Domain-Driven Image Generation using Limited Data