Zobrazeno 1 - 10
of 562
pro vyhledávání: '"Sun Yuwei"'
Publikováno v:
Nanophotonics, Vol 13, Iss 5, Pp 737-747 (2024)
Nonreciprocal thermal radiation can violate Kirchhoff’s law and exhibit different emissivity at symmetric polar angles relative to the normal direction. Realizing a mid-infrared broadband nonreciprocal thermal emitter with a wide emission angle ran
Externí odkaz:
https://doaj.org/article/eecb98b83ad542bb9d77c9bc77087293
Publikováno v:
Nanophotonics, Vol 12, Iss 15, Pp 3159-3164 (2023)
PbS colloidal quantum dots (CQDs) can be considered a promising lighting material, but their emission performance is mired by defect sites, strong photo-induced activity, and interaction with the environment. Here, we utilize periodic silicon metasur
Externí odkaz:
https://doaj.org/article/be97289f6c9d448fbb35f3bb78de9a5a
Publikováno v:
电力工程技术, Vol 41, Iss 5, Pp 21-30,84 (2022)
The modular multilevel matrix converter (M3C) is the core equipment for fractional frequency transmission system (FFTS). The AC-AC conversion of M3C leads to direct coupling of the ac electrical quantities at different frequencies,causing complex har
Externí odkaz:
https://doaj.org/article/71932286c0f44f128ec47ae55d018f59
Anomaly detection is an important function in IoT applications for finding outliers caused by abnormal events. Anomaly detection sometimes comes with high-frequency data sampling which should be carried out at Edge devices rather than Cloud. In this
Externí odkaz:
http://arxiv.org/abs/2407.11308
Neural networks encounter the challenge of Catastrophic Forgetting (CF) in continual learning, where new task learning interferes with previously learned knowledge. Existing data fine-tuning and regularization methods necessitate task identity inform
Externí odkaz:
http://arxiv.org/abs/2404.07518
Publikováno v:
E3S Web of Conferences, Vol 185, p 01082 (2020)
The S-CO2 power cycle has the advantages of compact structure and high energy density, which can be used to recover the waste heat of ship exhaust, thus improving the energy efficiency of ships and reducing emissions. The hybrid heat exchangers with
Externí odkaz:
https://doaj.org/article/e313aa4bc2d940e88d33ae924b069378
Emerging from the pairwise attention in conventional Transformers, there is a growing interest in sparse attention mechanisms that align more closely with localized, contextual learning in the biological brain. Existing studies such as the Coordinati
Externí odkaz:
http://arxiv.org/abs/2309.12862
Autor:
Sun, Yuwei
Meta-learning aims to develop algorithms that can learn from other learning algorithms to adapt to new and changing environments. This requires a model of how other learning algorithms operate and perform in different contexts, which is similar to re
Externí odkaz:
http://arxiv.org/abs/2305.12109
Trojan attacks embed perturbations in input data leading to malicious behavior in neural network models. A combination of various Trojans in different modalities enables an adversary to mount a sophisticated attack on multimodal learning such as Visu
Externí odkaz:
http://arxiv.org/abs/2304.00436
Autor:
Sun, Yuwei
Meta-learning usually refers to a learning algorithm that learns from other learning algorithms. The problem of uncertainty in the predictions of neural networks shows that the world is only partially predictable and a learned neural network cannot g
Externí odkaz:
http://arxiv.org/abs/2302.01020