Wei Fan

Orcid: 0000-0001-7656-445X

Affiliations:
  • University of Oxford, UK
  • University of Central Florida, FL, USA (PhD 2023)


According to our database1, Wei Fan authored at least 29 papers between 2020 and 2024.

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

Timeline

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Bibliography

2024
DEWP: Deep Expansion Learning for Wind Power Forecasting.
ACM Trans. Knowl. Discov. Data, April, 2024

Empowering Pre-Trained Language Models for Spatio-Temporal Forecasting via Decoupling Enhanced Discrete Reprogramming.
CoRR, 2024

Wills Aligner: A Robust Multi-Subject Brain Representation Learner.
CoRR, 2024

Addressing Distribution Shift in Time Series Forecasting with Instance Normalization Flows.
CoRR, 2024

Dual-stage Flows-based Generative Modeling for Traceable Urban Planning.
Proceedings of the 2024 SIAM International Conference on Data Mining, 2024

Decoupled Invariant Attention Network for Multivariate Time-series Forecasting.
Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence, 2024

HyDiscGAN: A Hybrid Distributed cGAN for Audio-Visual Privacy Preservation in Multimodal Sentiment Analysis.
Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence, 2024

FedGCS: A Generative Framework for Efficient Client Selection in Federated Learning via Gradient-based Optimization.
Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence, 2024

Reconstructing Missing Variables for Multivariate Time Series Forecasting via Conditional Generative Flows.
Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence, 2024

Deep Frequency Derivative Learning for Non-stationary Time Series Forecasting.
Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence, 2024

MLIP: Efficient Multi-Perspective Language-Image Pretraining with Exhaustive Data Utilization.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

PTaRL: Prototype-based Tabular Representation Learning via Space Calibration.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023
A primary and secondary feature interactive learning network for bone age assessment.
Biomed. Signal Process. Control., August, 2023

Interactive Reinforcement Learning for Feature Selection With Decision Tree in the Loop.
IEEE Trans. Knowl. Data Eng., 2023

Frequency-domain MLPs are More Effective Learners in Time Series Forecasting.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

FourierGNN: Rethinking Multivariate Time Series Forecasting from a Pure Graph Perspective.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Boosting Urban Prediction via Addressing Spatial-Temporal Distribution Shift.
Proceedings of the IEEE International Conference on Data Mining, 2023

Dish-TS: A General Paradigm for Alleviating Distribution Shift in Time Series Forecasting.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022
CFJLNet: Coarse and Fine Feature Joint Learning Network for Bone Age Assessment.
IEEE Trans. Instrum. Meas., 2022

Boosting Urban Traffic Speed Prediction via Integrating Implicit Spatial Correlations.
CoRR, 2022

Graph Soft-Contrastive Learning via Neighborhood Ranking.
CoRR, 2022

TransHER: Translating Knowledge Graph Embedding with Hyper-Ellipsoidal Restriction.
CoRR, 2022

Feature and Instance Joint Selection: A Reinforcement Learning Perspective.
Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022

DEPTS: Deep Expansion Learning for Periodic Time Series Forecasting.
Proceedings of the Tenth International Conference on Learning Representations, 2022

Multi-Graph Convolutional Recurrent Network for Fine-Grained Lane-Level Traffic Flow Imputation.
Proceedings of the IEEE International Conference on Data Mining, 2022

2021
AutoGFS: Automated Group-based Feature Selection via Interactive Reinforcement Learning.
Proceedings of the 2021 SIAM International Conference on Data Mining, 2021

Fair Graph Auto-Encoder for Unbiased Graph Representations with Wasserstein Distance.
Proceedings of the IEEE International Conference on Data Mining, 2021

2020
Simplifying Reinforced Feature Selection via Restructured Choice Strategy of Single Agent.
Proceedings of the 20th IEEE International Conference on Data Mining, 2020

AutoFS: Automated Feature Selection via Diversity-aware Interactive Reinforcement Learning.
Proceedings of the 20th IEEE International Conference on Data Mining, 2020


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