9 citations · 9 across the 2 of their papers we have counts for
2 papers
cs.LG2025
Temporal horizons in forecasting: a performance-learnability trade-off
Pau Vilimelis Aceituno, Jack William Miller, Noah Marti +2
When training autoregressive models to forecast dynamical systems, a critical question arises: how far into the future should the model be trained to predict for optimal performanc…
math.NA2024★ 9 cited
Differentiable Programming for Differential Equations: A Review
Facundo Sapienza, Jordi Bolibar, Frank Schäfer +8
The differentiable programming paradigm is a cornerstone of modern scientific computing. It refers to numerical methods for computing the gradient of a numerical model's output. Ma…