output
20192025
most citedDeep Anomaly Detection for Time-series Data in Industrial IoT: A Communication-Efficient On-device Federated Learning Approach

539 citations

13 papers

astro-ph.CO2025

Interacting scalar field dark matter and stepped dark radiation in an extended Wess-Zumino dark radiation model

Gang Liu

We extend the Wess-Zumino dark radiation (WZDR) model by replacing cold dark matter with scalar field dark matter and introducing a pure momentum coupling between the scalar field…

cs.LO2024

About enveloping algebras of direct sums

Gérard Henry Edmond Duchamp, Christophe Tollu, Jean-Gabriel Luque +1

We solve the PBW-like problem of normal ordering for enveloping algebras of direct sums.

cs.LG2024★ 11 cited

Distillation Enhanced Time Series Forecasting Network with Momentum Contrastive Learning

Haozhi Gao, Qianqian Ren, Jinbao Li

Contrastive representation learning is crucial in time series analysis as it alleviates the issue of data noise and incompleteness as well as sparsity of supervision signal. Howeve…

cond-mat.mes-hall2021★ 17 cited

Electric field induced injection and shift currents in zigzag graphene nanoribbons

Yadong Wei, Weiqi Li, Yongyuan Jiang +1

We theoretically investigate the one-color injection currents and shift currents in zigzag graphene nanoribbons with applying a static electric field across the ribbon, which break…

eess.IV2021★ 109 cited

FedDPGAN: Federated Differentially Private Generative Adversarial Networks Framework for the Detection of COVID-19 Pneumonia

Longling Zhang, Bochen Shen, Ahmed Barnawi +3

Existing deep learning technologies generally learn the features of chest X-ray data generated by Generative Adversarial Networks (GAN) to diagnose COVID-19 pneumonia. However, the…

cs.CV2021

Towards Accurate RGB-D Saliency Detection with Complementary Attention and Adaptive Integration

Hong-Bo Bi, Zi-Qi Liu, Kang Wang +3

Saliency detection based on the complementary information from RGB images and depth maps has recently gained great popularity. In this paper, we propose Complementary Attention and…