1 citations · 1 across the 2 of their papers we have counts for
2 papers
cs.LG2026
Selective Time Series Forecasting via Metalearning
Ricardo Inácio, Vitor Cerqueira, Marília Barandas +1
Deep learning methods have achieved state-of-the-art in time series forecasting, yet their accuracy varies considerably across samples, as some instances remain inherently difficul…
cs.LG2024★ 1 cited
Meta-learning and Data Augmentation for Stress Testing Forecasting Models
Ricardo Inácio, Vitor Cerqueira, Marília Barandas +1
The effectiveness of univariate forecasting models is often hampered by conditions that cause them stress. A model is considered to be under stress if it shows a negative behaviour…