Fang Yu

Orcid: 0000-0001-9670-0826

Affiliations:

Chinese Academy of Sciences, Institute of Computing Technology, Beijing, China
University of Chinese Academy of Sciences, School of Computer Science and Technology, Beijing, China

According to our database¹, Fang Yu authored at least 11 papers between 2015 and 2022.

Collaborative distances:

Dijkstra number² of five.
Erdős number³ of four.

Timeline

Legend:

Book

In proceedings

Article

PhD thesis

Dataset

Other

Bibliography

2022

Rec-AUNet: Attentive UNet for Reconstruction of ECG from BCG.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2022

Width & Depth Pruning for Vision Transformers.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021

EasiEdge: A Novel Global Deep Neural Networks Pruning Method for Efficient Edge Computing.

[BibT_eX]

[DOI]

IEEE Internet Things J., 2021

Gate Trimming: One-Shot Channel Pruning for Efficient Convolutional Neural Networks.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Acoustics, 2021

Length No Longer Matters: A Real Length Adaptive Arrhythmia Classification Model with Multi-Scale Convolution.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Acoustics, 2021

2020

TNAM: A tag-aware neural attention model for Top-N recommendation.

[BibT_eX]

[DOI]

Neurocomputing, 2020

HFP: Hardware-Aware Filter Pruning for Deep Convolutional Neural Networks Acceleration.

[BibT_eX]

[DOI]

Proceedings of the 25th International Conference on Pattern Recognition, 2020

EasiECG: A Novel Inter-Patient Arrhythmia Classification Method using ECG Waves.

[BibT_eX]

[DOI]

Proceedings of the 25th International Conference on Pattern Recognition, 2020

Tutor-Instructing Global Pruning for Accelerating Convolutional Neural Networks.

[BibT_eX]

[DOI]

Fang Yu

Li Cui

Proceedings of the ECAI 2020 - 24th European Conference on Artificial Intelligence, 29 August-8 September 2020, Santiago de Compostela, Spain, August 29 - September 8, 2020, 2020

Calibration-free Blood Pressure Assessment Using An Integrated Deep Learning Method.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2020

2015

A method for estimating and removing streaking artifacts in quantitative susceptibility mapping.