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- Chinese Academy of SciencesCN54 papers
- Sun Yat-sen UniversityCN45 papers
- National Central UniversityTW38 papers
- State Key Laboratory of Lunar and Planetary SciencesMO35 papers
- Purple Mountain ObservatoryCN29 papers
- Centre National de la Recherche ScientifiqueFR22 papers
- University of Chinese Academy of SciencesCN20 papers
- Space Science InstituteUS19 papers
- Jet Propulsion LaboratoryUS17 papers
- Nanjing UniversityCN16 papers
- National Astronomical ObservatoriesCN16 papers
- University of Maryland, College ParkUS16 papers
8 papers · 1 filter
In-Context Source and Channel Coding
Ziqiong Wang, Tianqi Ren, Rongpeng Li +2
Separate Source-Channel Coding (SSCC) remains attractive for text transmission due to its modularity and compatibility with mature entropy coders and powerful channel codes. Howeve…
LNN-PINN: A Unified Physics-Only Training Framework with Liquid Residual Blocks
Ze Tao, Hanxuan Wang, Fujun Liu
Physics-informed neural networks (PINNs) have attracted considerable attention for their ability to integrate partial differential equation priors into deep learning frameworks; ho…
DeepGrav: Anomalous Gravitational-Wave Detection Through Deep Latent Features
Jianqi Yan, Alex P. Leung, Zhiyuan Pei +2
This work introduces a novel deep learning-based approach for gravitational wave anomaly detection, aiming to overcome the limitations of traditional matched filtering techniques i…
Short-Term Electricity-Load Forecasting by Deep Learning: A Comprehensive Survey
Qi Dong, Rubing Huang, Chenhui Cui +4
Short-Term Electricity-Load Forecasting (STELF) refers to the prediction of the immediate demand (in the next few hours to several days) for the power system. Various external fact…
Guaranteed Tensor Recovery Fused Low-rankness and Smoothness
Hailin Wang, Jiangjun Peng, Wenjin Qin +2
The tensor data recovery task has thus attracted much research attention in recent years. Solving such an ill-posed problem generally requires to explore intrinsic prior structures…
Compacting Deep Neural Networks for Internet of Things: Methods and Applications
Ke Zhang, Hanbo Ying, Hong-Ning Dai +4
Deep Neural Networks (DNNs) have shown great success in completing complex tasks. However, DNNs inevitably bring high computational cost and storage consumption due to the complexi…