Peng Zhu

Orcid: 0000-0001-9558-3787

Affiliations:

Tongji University, Department of Computer Science and Technology, Shanghai, China
East China Normal University, School of Data Science and Engineering, Shanghai, China (PhD 2023)

According to our database¹, Peng Zhu authored at least 20 papers between 2021 and 2026.

Collaborative distances:

Dijkstra number² of four.
Erdős number³ of four.

Timeline

Legend:

Book In proceedings Article PhD thesis Dataset Other

Bibliography

2026

PeakFocus: Bridging Peak Localization and Intensity Regression via a Unified Multi-Scale Framework for Electricity Load Forecasting.

[BibT_eX]

[DOI]

CoRR, May, 2026

Delay-Aware Graph Neural Stochastic Differential Equations for Financial Time Series Modeling and Forecasting.

[BibT_eX]

[DOI]

Proceedings of the ACM Web Conference 2026, 2026

Credit and Power Co-evolution Modeling with Dynamic Graph Learning.

[BibT_eX]

[DOI]

Proceedings of the ACM Web Conference 2026, 2026

SoftHist: Teaching Graph Injection Attackers to Camouflage with Memory.

[BibT_eX]

[DOI]

Proceedings of the Nineteenth ACM International Conference on Web Search and Data Mining, 2026

Role Perceptual Augmented Temporal Graph Network for Related-party Transaction Detection.

[BibT_eX]

[DOI]

Proceedings of the Fortieth AAAI Conference on Artificial Intelligence, 2026

2025

Financial Time Series Prediction With Multi-Granularity Graph Augmented Learning.

[BibT_eX]

[DOI]

IEEE Trans. Knowl. Data Eng., November, 2025

MCI-GRU: Stock prediction model based on multi-head cross-attention and improved GRU.

[BibT_eX]

[DOI]

Neurocomputing, 2025

A Risk Prediction Model for Real Estate Corporations Using High-Target Semantic BERT and Improved GRU.

[BibT_eX]

[DOI]

Proceedings of the 2025 IEEE International Conference on Acoustics, 2025

Adaptive Multi-Scale Decomposition Framework for Time Series Forecasting.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Ninth AAAI Conference on Artificial Intelligence, 2025

2024

Predicting stock market trends with self-supervised learning.

[BibT_eX]

[DOI]

Neurocomputing, February, 2024

Asymmetric Graph-Based Deep Reinforcement Learning for Portfolio Optimization.

[BibT_eX]

[DOI]

Proceedings of the Machine Learning and Knowledge Discovery in Databases. Applied Data Science Track, 2024

NGDRL: A Dynamic News Graph-Based Deep Reinforcement Learning Framework for Portfolio Optimization.

[BibT_eX]

[DOI]

Proceedings of the Database Systems for Advanced Applications, 2024

LSR-IGRU: Stock Trend Prediction Based on Long Short-Term Relationships and Improved GRU.

[BibT_eX]

[DOI]

Proceedings of the 33rd ACM International Conference on Information and Knowledge Management, 2024

Dynamic Graph-based Deep Reinforcement Learning with Long and Short-term Relation Modeling for Portfolio Optimization.

[BibT_eX]

[DOI]

Proceedings of the 33rd ACM International Conference on Information and Knowledge Management, 2024

2023

MCA-NER: Multi-Contextualized Adversarial-Based Attentional Deep Neural Network for Named Entity Recognition.

[BibT_eX]

[DOI]

Int. J. Pattern Recognit. Artif. Intell., September, 2023

Adversarial Multi-task Learning for Efficient Chinese Named Entity Recognition.

[BibT_eX]

[DOI]

ACM Trans. Asian Low Resour. Lang. Inf. Process., 2023

2022

Leveraging enterprise knowledge graph to infer web events' influences via self-supervised learning.

[BibT_eX]

[DOI]

J. Web Semant., 2022

Improving Chinese Named Entity Recognition by Large-Scale Syntactic Dependency Graph.

[BibT_eX]

[DOI]

IEEE ACM Trans. Audio Speech Lang. Process., 2022

SI-News: Integrating social information for news recommendation with attention-based graph convolutional network.

[BibT_eX]

[DOI]

Neurocomputing, 2022

2021

ZH-NER: Chinese Named Entity Recognition with Adversarial Multi-task Learning and Self-Attentions.

[BibT_eX]

[DOI]

Proceedings of the Database Systems for Advanced Applications, 2021

Peng Zhu

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