Ming Jin

Orcid: 0000-0002-6833-4811

Affiliations:
  • Monash University, Australia


According to our database1, Ming Jin authored at least 25 papers between 2019 and 2024.

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

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
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Other 

Links

Online presence:

On csauthors.net:

Bibliography

2024
Foundation Models for Time Series Analysis: A Tutorial and Survey.
CoRR, 2024

Attractor Memory for Long-Term Time Series Forecasting: A Chaos Perspective.
CoRR, 2024

Position Paper: What Can Large Language Models Tell Us about Time Series Analysis.
CoRR, 2024

Graph Spatiotemporal Process for Multivariate Time Series Anomaly Detection with Missing Values.
CoRR, 2024

HiMTM: Hierarchical Multi-Scale Masked Time Series Modeling for Long-Term Forecasting.
CoRR, 2024

2023
Generative and Contrastive Self-Supervised Learning for Graph Anomaly Detection.
IEEE Trans. Knowl. Data Eng., December, 2023

Multivariate Time Series Forecasting With Dynamic Graph Neural ODEs.
IEEE Trans. Knowl. Data Eng., September, 2023

Graph Self-Supervised Learning: A Survey.
IEEE Trans. Knowl. Data Eng., June, 2023

Large Models for Time Series and Spatio-Temporal Data: A Survey and Outlook.
CoRR, 2023

Time-LLM: Time Series Forecasting by Reprogramming Large Language Models.
CoRR, 2023

Correlation-aware Spatial-Temporal Graph Learning for Multivariate Time-series Anomaly Detection.
CoRR, 2023

A Survey on Graph Neural Networks for Time Series: Forecasting, Classification, Imputation, and Anomaly Detection.
CoRR, 2023

Self-Supervised Learning for Time Series Analysis: Taxonomy, Progress, and Prospects.
CoRR, 2023

Towards Complex Dynamic Physics System Simulation with Graph Neural ODEs.
CoRR, 2023

How Expressive are Spectral-Temporal Graph Neural Networks for Time Series Forecasting?
CoRR, 2023

Geometric Relational Embeddings: A Survey.
CoRR, 2023

2022
From Unsupervised to Few-shot Graph Anomaly Detection: A Multi-scale Contrastive Learning Approach.
CoRR, 2022

Neural Temporal Walks: Motif-Aware Representation Learning on Continuous-Time Dynamic Graphs.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2021
Towards Graph Self-Supervised Learning with Contrastive Adjusted Zooming.
CoRR, 2021

Graph Self-Supervised Learning: A Survey.
CoRR, 2021

Multi-Scale Contrastive Siamese Networks for Self-Supervised Graph Representation Learning.
Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021

ANEMONE: Graph Anomaly Detection with Multi-Scale Contrastive Learning.
Proceedings of the CIKM '21: The 30th ACM International Conference on Information and Knowledge Management, Virtual Event, Queensland, Australia, November 1, 2021

2020
Optimized Coefficient Vector and Sparse Representation-Based Classification Method for Face Recognition.
IEEE Access, 2020

Searching Correlated Patterns From Graph Streams.
IEEE Access, 2020

2019
A Clickthrough Rate Prediction Algorithm Based on Users' Behaviors.
IEEE Access, 2019


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