6 citations · 7 across the 4 of their papers we have counts for
4 papers
Neural Conformal Control for Time Series Forecasting
Ruipu Li, Alexander Rodríguez
We introduce a neural network conformal prediction method for time series that enhances adaptivity in non-stationary environments. Our approach acts as a neural controller designed…
Learning Graph Structures and Uncertainty for Accurate and Calibrated Time-series Forecasting
Harshavardhan Kamarthi, Lingkai Kong, Alexander Rodriguez +2
Multi-variate time series forecasting is an important problem with a wide range of applications. Recent works model the relations between time-series as graphs and have shown that…
When Rigidity Hurts: Soft Consistency Regularization for Probabilistic Hierarchical Time Series Forecasting
Harshavardhan Kamarthi, Lingkai Kong, Alexander Rodríguez +2
Probabilistic hierarchical time-series forecasting is an important variant of time-series forecasting, where the goal is to model and forecast multivariate time-series that have un…
Data-Centric Epidemic Forecasting: A Survey
Alexander Rodríguez, Harshavardhan Kamarthi, Pulak Agarwal +4
The COVID-19 pandemic has brought forth the importance of epidemic forecasting for decision makers in multiple domains, ranging from public health to the economy as a whole. While…