5 citations · 8 across the 4 of their papers we have counts for
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cs.LG2025★ 1 cited
Conservation-informed Graph Learning for Spatiotemporal Dynamics Prediction
Yuan Mi, Pu Ren, Hongteng Xu +6
Data-centric methods have shown great potential in understanding and predicting spatiotemporal dynamics, enabling better design and control of the object system. However, deep lear…
cs.LG2024
Model Balancing Helps Low-data Training and Fine-tuning
Zihang Liu, Yuanzhe Hu, Tianyu Pang +3
Recent advances in foundation models have emphasized the need to align pre-trained models with specialized domains using small, curated datasets. Studies on these foundation models…
cs.LG2020★ 2 cited
Incremental Bayesian tensor learning for structural monitoring data imputation and response forecasting
Pu Ren, Xinyu Chen, Lijun Sun +1
There has been increased interest in missing sensor data imputation, which is ubiquitous in the field of structural health monitoring (SHM) due to discontinuous sensing caused by s…