60 citations · 132 across the 25 of their papers we have counts for
3 papers · 1 filter
AcTune: Uncertainty-aware Active Self-Training for Semi-Supervised Active Learning with Pretrained Language Models
Yue Yu, Lingkai Kong, Jieyu Zhang +2
While pre-trained language model (PLM) fine-tuning has achieved strong performance in many NLP tasks, the fine-tuning stage can be still demanding in labeled data. Recent works hav…
CAMul: Calibrated and Accurate Multi-view Time-Series Forecasting
Harshavardhan Kamarthi, Lingkai Kong, Alexander Rodríguez +2
Probabilistic time-series forecasting enables reliable decision making across many domains. Most forecasting problems have diverse sources of data containing multiple modalities an…
When in Doubt: Neural Non-Parametric Uncertainty Quantification for Epidemic Forecasting
Harshavardhan Kamarthi, Lingkai Kong, Alexander Rodríguez +2
Accurate and trustworthy epidemic forecasting is an important problem that has impact on public health planning and disease mitigation. Most existing epidemic forecasting models di…