27 citations · 31 across the 11 of their papers we have counts for
3 papers · 1 filter
Uncertainty Estimation for Super-Resolution using ESRGAN
Maniraj Sai Adapa, Marco Zullich, Matias Valdenegro-Toro
Deep Learning-based image super-resolution (SR) has been gaining traction with the aid of Generative Adversarial Networks. Models like SRGAN and ESRGAN are constantly ranked betwee…
Upside-Down Reinforcement Learning for More Interpretable Optimal Control
Juan Cardenas-Cartagena, Massimiliano Falzari, Marco Zullich +1
Model-Free Reinforcement Learning (RL) algorithms either learn how to map states to expected rewards or search for policies that can maximize a certain performance function. Model-…
Unified Uncertainties: Combining Input, Data and Model Uncertainty into a Single Formulation
Matias Valdenegro-Toro, Ivo Pascal de Jong, Marco Zullich
Modelling uncertainty in Machine Learning models is essential for achieving safe and reliable predictions. Most research on uncertainty focuses on output uncertainty (predictions),…