7 citations · 12 across the 2 of their papers we have counts for
3 papers
cs.LG2022★ 5 cited
Comparison of Uncertainty Quantification with Deep Learning in Time Series Regression
Levente Foldesi, Matias Valdenegro-Toro
Increasingly high-stakes decisions are made using neural networks in order to make predictions. Specifically, meteorologists and hedge funds apply these techniques to time series d…
cs.LG2022★ 7 cited
A Deeper Look into Aleatoric and Epistemic Uncertainty Disentanglement
Matias Valdenegro-Toro, Daniel Saromo
Neural networks are ubiquitous in many tasks, but trusting their predictions is an open issue. Uncertainty quantification is required for many applications, and disentangled aleato…
cs.CV2021
I Find Your Lack of Uncertainty in Computer Vision Disturbing
Matias Valdenegro-Toro
Neural networks are used for many real world applications, but often they have problems estimating their own confidence. This is particularly problematic for computer vision applic…