Zobrazeno 1 - 10
of 726
pro vyhledávání: '"Zhu, YiFei"'
The kinetics of plasma assisted low temperature oxidation of C3H8O2Ar mixtures have been studied in a wide specific deposition energy with the help of nanosecond repetitively pulsed discharge. Two types of nanosecond pulsed plasma sources, the nanose
Externí odkaz:
http://arxiv.org/abs/2407.21295
Large pre-trained models have exhibited remarkable achievements across various domains. The substantial training costs associated with these models have led to wide studies of fine-tuning for effectively harnessing their capabilities in solving downs
Externí odkaz:
http://arxiv.org/abs/2407.17533
We introduce Topological Offsets, a novel approach to generate manifold and self-intersection-free offset surfaces that are topologically equivalent to an offset infinitesimally close to the surface. Our approach, by construction, creates a manifold,
Externí odkaz:
http://arxiv.org/abs/2407.07725
Autor:
Wang, Zhe, Zhu, Yifei
Neural Radiance Fields (NeRF) is an emerging technique to synthesize 3D objects from 2D images with a wide range of potential applications. However, rendering existing NeRF models is extremely computation intensive, making it challenging to support r
Externí odkaz:
http://arxiv.org/abs/2406.16068
Due to rapid advancements in deep learning techniques, the demand for large-volume high-quality databases grows significantly in chemical research. We developed a quantum-chemistry database that includes 443,106 small organic molecules with sizes up
Externí odkaz:
http://arxiv.org/abs/2406.02341
The escalating influx of data generated by networked edge devices, coupled with the growing awareness of data privacy, has restricted the traditional data analytics workflow, where the edge data are gathered by a centralized server to be further util
Externí odkaz:
http://arxiv.org/abs/2404.12666
The emerging Web 3.0 paradigm aims to decentralize existing web services, enabling desirable properties such as transparency, incentives, and privacy preservation. However, current Web 3.0 applications supported by blockchain infrastructure still can
Externí odkaz:
http://arxiv.org/abs/2402.09736
Autor:
Huang, Jiahe, Zhu, Yifei
Low latency and high synchronization among users are critical for emerging multi-user virtual interaction applications. However, the existing ground-based cloud solutions are naturally limited by the complex ground topology and fiber speeds, making i
Externí odkaz:
http://arxiv.org/abs/2402.09720
Federated learning (FL) has emerged as a prevalent distributed machine learning scheme that enables collaborative model training without aggregating raw data. Cloud service providers further embrace Federated Learning as a Service (FLaaS), allowing d
Externí odkaz:
http://arxiv.org/abs/2402.09715
Federated training of Graph Neural Networks (GNN) has become popular in recent years due to its ability to perform graph-related tasks under data isolation scenarios while preserving data privacy. However, graph heterogeneity issues in federated GNN
Externí odkaz:
http://arxiv.org/abs/2309.09517