Combining graph neural networks and spatio-temporal disease models to improve the prediction of weekly COVID-19 cases in Germany
During 2020, the infection rate of COVID-19 has been investigated by many scholars from
different research fields. In this context, reliable and interpretable forecasts of disease …
different research fields. In this context, reliable and interpretable forecasts of disease …
A new PHO-rmula for improved performance of semi-structured networks
D Rügamer - International Conference on Machine Learning, 2023 - proceedings.mlr.press
Recent advances to combine structured regression models and deep neural networks for
better interpretability, more expressiveness, and statistically valid uncertainty quantification …
better interpretability, more expressiveness, and statistically valid uncertainty quantification …
Semi-structured distributional regression
Combining additive models and neural networks allows to broaden the scope of statistical
regression and extend deep learning-based approaches by interpretable structured additive …
regression and extend deep learning-based approaches by interpretable structured additive …
Bayesian Semi-structured Subspace Inference
Semi-structured regression models enable the joint modeling of interpretable structured and
complex unstructured feature effects. The structured model part is inspired by statistical …
complex unstructured feature effects. The structured model part is inspired by statistical …
Answering regular path queries using views
D Calvanese, G De Giacomo… - Proceedings of 16th …, 2000 - ieeexplore.ieee.org
Query answering using views amounts to computing the answer to a query having
information only on the extension of a set of views. This problem is relevant in several fields …
information only on the extension of a set of views. This problem is relevant in several fields …
[图书][B] Bringing together computational and linguistic models of implicit role interpretation
TJ O'Gorman - 2019 - search.proquest.com
This dissertation studies implicit semantic roles–instances where a participant is not
explicitly stated in the text, such as the arguments in “∅ you eat∅ food yet?”. It focuses upon …
explicitly stated in the text, such as the arguments in “∅ you eat∅ food yet?”. It focuses upon …
Generalized additive neural network with flexible parametric link function: model estimation using simulated and real clinical data
C Brás-Geraldes, A Papoila, P Xufre - Neural Computing and Applications, 2019 - Springer
Artificial neural networks have been proposed in medical research as an alternative to some
regression models such as the generalized linear models, being the multilayer perceptron …
regression models such as the generalized linear models, being the multilayer perceptron …
Odds ratio function estimation using a generalized additive neural network
C Brás-Geraldes, A Papoila, P Xufre - Neural Computing and Applications, 2020 - Springer
In biomedical research, generalized artificial neural networks (GANNs) have been proposed
as an alternative to a multi-layer perceptron owing to their greater ability to generate more …
as an alternative to a multi-layer perceptron owing to their greater ability to generate more …
The Partial Response Network: a neural network nomogram
PJG Lisboa, S Ortega-Martorell, S Cashman… - arXiv preprint arXiv …, 2019 - arxiv.org
Among interpretable machine learning methods, the class of Generalised Additive Neural
Networks (GANNs) is referred to as Self-Explaining Neural Networks (SENN) because of the …
Networks (GANNs) is referred to as Self-Explaining Neural Networks (SENN) because of the …
Towards interpretable machine learning for clinical decision support
B Walters, S Ortega-Martorell, I Olier… - … Joint Conference on …, 2022 - ieeexplore.ieee.org
A major challenge in delivering reliable and trustworthy computational intelligence for
practical applications in clinical medicine is interpretability. This aspect of machine learning …
practical applications in clinical medicine is interpretability. This aspect of machine learning …