Kun Yi

Orcid: 0000-0002-9980-6033

Affiliations:
  • Beijing Institute of Technology, School of Computer Science and Technology, Beijing, China


According to our database1, Kun Yi authored at least 16 papers between 2022 and 2024.

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

Timeline

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Bibliography

2024
Deep Coupling Network for Multivariate Time Series Forecasting.
ACM Trans. Inf. Syst., September, 2024

Learning Informative Representation for Fairness-Aware Multivariate Time-Series Forecasting: A Group-Based Perspective.
IEEE Trans. Knowl. Data Eng., June, 2024

Robust Multivariate Time Series Forecasting against Intra- and Inter-Series Transitional Shift.
CoRR, 2024

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

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

Frequency Spectrum Is More Effective for Multimodal Representation and Fusion: A Multimodal Spectrum Rumor Detector.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023
Neural Time Series Analysis with Fourier Transform: A Survey.
CoRR, 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

2022
Edge-Varying Fourier Graph Networks for Multivariate Time Series Forecasting.
CoRR, 2022

Distributional Drift Adaptation with Temporal Conditional Variational Autoencoder for Multivariate Time Series Forecasting.
CoRR, 2022

CATN: Cross Attentive Tree-Aware Network for Multivariate Time Series Forecasting.
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022


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