Jiahao Ji

Orcid: 0000-0003-3029-2262

According to our database1, Jiahao Ji authored at least 13 papers between 2020 and 2024.

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

Timeline

Legend:

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Links

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Bibliography

2024
AirPhyNet: Harnessing Physics-Guided Neural Networks for Air Quality Prediction.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

Weight Light, Hear Right: Heart Sound Classification with a Low-Complexity Model.
Proceedings of the 32nd European Signal Processing Conference, 2024

Advancing Re-Ranking with Multimodal Fusion and Target-Oriented Auxiliary Tasks in E-Commerce Search.
Proceedings of the 33rd ACM International Conference on Information and Knowledge Management, 2024

2023
Traffic Flow Prediction Based on Spatiotemporal Potential Energy Fields.
IEEE Trans. Knowl. Data Eng., September, 2023

Self-Supervised Deconfounding Against Spatio-Temporal Shifts: Theory and Modeling.
CoRR, 2023

Multi-Factor Spatio-Temporal Prediction based on Graph Decomposition Learning.
CoRR, 2023

Enhancing New Intent Discovery via Robust Neighbor-based Contrastive Learning.
Proceedings of the 24th Annual Conference of the International Speech Communication Association, 2023

Spatio-Temporal Self-Supervised Learning for Traffic Flow Prediction.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022
DialCSP: A Two-Stage Attention-Based Model for Customer Satisfaction Prediction in E-commerce Customer Service.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2022

Precision CityShield Against Hazardous Chemicals Threats via Location Mining and Self-Supervised Learning.
Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

STDEN: Towards Physics-Guided Neural Networks for Traffic Flow Prediction.
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2020
Primary Categorizing and Masking Cerebral Small Vessel Disease Based on "Deep Learning System".
Frontiers Neuroinformatics, 2020

Interpretable Spatiotemporal Deep Learning Model for Traffic Flow Prediction based on Potential Energy Fields.
Proceedings of the 20th IEEE International Conference on Data Mining, 2020


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