2 citations · 2 across the 2 of their papers we have counts for
2 papers
cs.CL2024★ 2 cited
Curating Grounded Synthetic Data with Global Perspectives for Equitable AI
Elin Törnquist, Robert Alexander Caulk
The development of robust AI models relies heavily on the quality and variety of training data available. In fields where data scarcity is prevalent, synthetic data generation offe…
cs.LG2023
Balancing Computational Efficiency and Forecast Error in Machine Learning-based Time-Series Forecasting: Insights from Live Experiments on Meteorological Nowcasting
Elin Törnquist, Wagner Costa Santos, Timothy Pogue +2
Machine learning for time-series forecasting remains a key area of research. Despite successful application of many machine learning techniques, relating computational efficiency t…