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Massive stars end their life as core-collapse supernovae, amongst which some extremes are Type Ic broad-lined supernovae associated with long-duration gamma-ray bursts (LGRBs) having powerful relativistic jets. Their less-extreme brethren make unsucc
Externí odkaz:
http://arxiv.org/abs/2410.02315
In the framework of general relativity, the dynamics of a general barotropic fluid are coupled to the Einstein equations, which govern the structure of the underlying spacetime. We establish a priori estimates and well-posedness in Sobolev spaces for
Externí odkaz:
http://arxiv.org/abs/2410.01616
Autor:
Li, Muyang, Xiong, Juming, Deng, Ruining, Yao, Tianyuan, Tyree, Regina N, Hiremath, Girish, Huo, Yuankai
Endoscopy is a crucial tool for diagnosing the gastrointestinal tract, but its effectiveness is often limited by a narrow field of view and the dynamic nature of the internal environment, especially in the esophagus, where complex and repetitive patt
Externí odkaz:
http://arxiv.org/abs/2410.01148
Robots' ability to follow language instructions and execute diverse 3D tasks is vital in robot learning. Traditional imitation learning-based methods perform well on seen tasks but struggle with novel, unseen ones due to variability. Recent approache
Externí odkaz:
http://arxiv.org/abs/2409.20154
Autor:
Huo, Pingyi, Devulapally, Anusha, Maruf, Hasan Al, Park, Minseo, Nair, Krishnakumar, Arunachalam, Meena, Akbulut, Gulsum Gudukbay, Kandemir, Mahmut Taylan, Narayanan, Vijaykrishnan
Deep Learning Recommendation Models (DLRMs) have become increasingly popular and prevalent in today's datacenters, consuming most of the AI inference cycles. The performance of DLRMs is heavily influenced by available bandwidth due to their large vec
Externí odkaz:
http://arxiv.org/abs/2409.16633
Distributed energy resources (DERs) are gaining prominence due to their advantages in improving energy efficiency, reducing carbon emissions, and enhancing grid resilience. Despite the increasing deployment, the potential of DERs has yet to be fully
Externí odkaz:
http://arxiv.org/abs/2409.14499
Accurately reconstructing dense and semantically annotated 3D meshes from monocular images remains a challenging task due to the lack of geometry guidance and imperfect view-dependent 2D priors. Though we have witnessed recent advancements in implici
Externí odkaz:
http://arxiv.org/abs/2409.14019
Autor:
Li, Zhiyuan, Yao, Tianyuan, Kanakaraj, Praitayini, Gao, Chenyu, Bao, Shunxing, Zuo, Lianrui, Kim, Michael E., Newlin, Nancy R., Rudravaram, Gaurav, Khairi, Nazirah M., Huo, Yuankai, Schilling, Kurt G., Kukull, Walter A., Toga, Arthur W., Archer, Derek B., Hohman, Timothy J., Landman, Bennett A.
An incomplete field-of-view (FOV) in diffusion magnetic resonance imaging (dMRI) can severely hinder the volumetric and bundle analyses of whole-brain white matter connectivity. Although existing works have investigated imputing the missing regions u
Externí odkaz:
http://arxiv.org/abs/2409.13846
Autor:
Huang, Junjie, Jiang, Zhihan, Liu, Jinyang, Huo, Yintong, Gu, Jiazhen, Chen, Zhuangbin, Feng, Cong, Dong, Hui, Yang, Zengyin, Lyu, Michael R.
Logs are imperative in the maintenance of online service systems, which often encompass important information for effective failure mitigation. While existing anomaly detection methodologies facilitate the identification of anomalous logs within exte
Externí odkaz:
http://arxiv.org/abs/2409.13561
Anomaly detection is an important problem in many application areas, such as network security. Many deep learning methods for unsupervised anomaly detection produce good empirical performance but lack theoretical guarantees. By casting anomaly detect
Externí odkaz:
http://arxiv.org/abs/2409.08521