activity
20142023
most citedFUTURE-AI: International consensus guideline for trustworthy and deployable artificial intelligence in healthcare

39 citations · 78 across the 12 of their papers we have counts for

collaborators

14 papers

cs.CY2023★ 39 cited

FUTURE-AI: International consensus guideline for trustworthy and deployable artificial intelligence in healthcare

Karim Lekadir, Aasa Feragen, Abdul Joseph Fofanah +117

Despite major advances in artificial intelligence (AI) for medicine and healthcare, the deployment and adoption of AI technologies remain limited in real-world clinical practice. I…

cs.LG2023

A Scalable and Efficient Iterative Method for Copying Machine Learning Classifiers

Nahuel Statuto, Irene Unceta, Jordi Nin +1

Differential replication through copying refers to the process of replicating the decision behavior of a machine learning model using another model that possesses enhanced features…

cs.LG2023

Importance attribution in neural networks by means of persistence landscapes of time series

Aina Ferrà, Carles Casacuberta, Oriol Pujol

We propose and implement a method to analyze time series with a neural network using a matrix of area-normalized persistence landscapes obtained through topological data analysis.…

math.AT2022★ 1 cited

Reconstruction of univariate functions from directional persistence diagrams

Aina Ferrà, Carles Casacuberta, Oriol Pujol

We describe a method for approximating a single-variable function using persistence diagrams of sublevel sets of from height functions in different directions. We provide a…

cs.LG2022★ 1 cited

Training Thinner and Deeper Neural Networks: Jumpstart Regularization

Carles Riera, Camilo Rey, Thiago Serra +2

Neural networks are more expressive when they have multiple layers. In turn, conventional training methods are only successful if the depth does not lead to numerical issues such a…

cs.LG2021

Quantile Encoder: Tackling High Cardinality Categorical Features in Regression Problems

Carlos Mougan, David Masip, Jordi Nin +1

Regression problems have been widely studied in machinelearning literature resulting in a plethora of regression models and performance measures. However, there are few techniques…