LLM Meeting Decision Trees on Tabular Data.
CoRR, May, 2025
Latte: Transfering LLMs' Latent-level Knowledge for Few-shot Tabular Learning.
CoRR, May, 2025
MedGNN: Towards Multi-resolution Spatiotemporal Graph Learning for Medical Time Series Classification.
CoRR, February, 2025
Towards Multi-resolution Spatiotemporal Graph Learning for Medical Time Series Classification.
Proceedings of the ACM on Web Conference 2025, 2025
DRL: Decomposed Representation Learning for Tabular Anomaly Detection.
Proceedings of the Thirteenth International Conference on Learning Representations, 2025
Enhancing Generalizability in Molecular Conformation Generation with METRIZATION-Informed Geometric Diffusion Pretraining.
Proceedings of the AAAI-25, Sponsored by the Association for the Advancement of Artificial Intelligence, February 25, 2025
Deep Frequency Derivative Learning for Non-stationary Time Series Forecasting.
Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence, 2024
PTaRL: Prototype-based Tabular Representation Learning via Space Calibration.
Proceedings of the Twelfth International Conference on Learning Representations, 2024
Single Cell Gene Expression Prediction via Prototype-based Proximal Neural Factorization.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2024
Web-based Long-term Spine Treatment Outcome Forecasting.
Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023
UADB: Unsupervised Anomaly Detection Booster.
Proceedings of the 39th IEEE International Conference on Data Engineering, 2023
A continuous glucose monitoring measurements forecasting approach via sporadic blood glucose monitoring.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2022
IMBENS: Ensemble Class-imbalanced Learning in Python.
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CoRR, 2021