Yu Zhang

Affiliations:
  • University of Sheffield, Department of Computer Science, UK


According to our database1, Yu Zhang authored at least 20 papers between 2020 and 2025.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

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In proceedings 
Article 
PhD thesis 
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Links

On csauthors.net:

Bibliography

2025
KG-FGNN: Knowledge-guided GNN Foundation Model for Fertilisation-oriented Soil GHG Flux Prediction.
CoRR, June, 2025

Exploring the Feasibility of Deep Learning Models for Long-term Disease Prediction: A Case Study for Wheat Yellow Rust in England.
CoRR, January, 2025

TMTCIL-st: Spatio-Temporal Tensor Multi-Task Continuous Incremental Learning for Multi-Fertiliser Management.
Proceedings of the IEEE International Conference on Industrial Technology, 2025

2024
ParallelFarm: An AI-Enabled Sustainable Farming Management System for Carbon Neutrality.
Proceedings of the 22nd IEEE International Conference on Industrial Informatics, 2024

Learning Interpretable Continuous Representation for Alzheimer's Disease Classification.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2024

Adaptive Multi-Cognitive Objective Temporal Task Approach for Predicting AD Progression.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2024

2023
Corrigendum to 'Sustainable fertilisation management via tensor multi-task learning using multi-dimensional agricultural data': [Journal of Industrial Informatic Integration, Vol 34, August (2023) start page-end page].
J. Ind. Inf. Integr., October, 2023

Efficient multi-task learning with adaptive temporal structure for progression prediction.
Neural Comput. Appl., August, 2023

Sustainable fertilisation management via tensor multi-task learning using multi-dimensional agricultural data.
J. Ind. Inf. Integr., August, 2023

Integrating Automatic Temporal Relation Graph into Multi-Task Learning for Alzheimer's Disease Progression Prediction.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2023

Empirical Analysis of Regularised Multi-Task Learning for Modelling Alzheimer's Disease Progression.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2023

Spatio-Temporal Similarity Measure based Multi-Task Learning for Predicting Alzheimer's Disease Progression using MRI Data.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2023

Robust Temporal Smoothness in Multi-Task Learning.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022
Spatio-temporal Tensor Multi-Task Learning for Precision Fertilisation with Real-world Agricultural Data.
Proceedings of the IECON 2022, 2022

Spatio-temporal Tensor Multi-Task Learning for Predicting Alzheimer's Disease in a Longitudinal study.
Proceedings of the 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society, 2022

Multi-task Learning with Adaptive Global Temporal Structure for Predicting Alzheimer's Disease Progression.
Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022

Modeling Alzheimer's Disease Progression via Amalgamated Magnitude-Direction Brain Structure Variation Quantification and Tensor Multi-task Learning.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2022

2021
Modeling Disease Progression Flexibly with Nonlinear Disease Structure via Multi-task Learning.
Proceedings of the 17th International Conference on Mobility, Sensing and Networking, 2021

Tensor Multi-Task Learning for Predicting Alzheimer's Disease Progression using MRI data with Spatio-temporal Similarity Measurement.
Proceedings of the 19th IEEE International Conference on Industrial Informatics, 2021

2020
Visual Analysis of Biomarkers Selected via Multi-Task Learning for Modeling Alzheimer's Disease Progression.
Proceedings of the IEEE International Conference on Parallel & Distributed Processing with Applications, 2020


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