Aug 12, 2024 · We present an attempt at unifying points of view and analyses of these objects coming from the social sciences, statistics, probability and physics communities.

7 days ago · We propose a novel framework for providing a non-parametric dynamic network model--based on a mixture of coupled hierarchical Dirichlet processes-- based on ...

Aug 26, 2024 · A professionally curated list of awesome Conformal Prediction videos, tutorials, books, papers, PhD and MSc theses, articles and open-source libraries.

Aug 23, 2024 · Detecting spacecraft anomalies using lstms and nonparametric dynamic thresholding. ... Link Prediction Based on Graph Neural Networks. In Advances in Neural ...

Aug 12, 2024 · We develop a method for deep learning inference using knockoffs, DeepLINK, to achieve the goal of variable selection with controlled error rate in deep ...

Aug 24, 2024 · Nonparametric bayes dynamic modelling of relational data. Biometrika, 101(4): ... A review of dynamic network models with latent variables. Statistics ...

Aug 19, 2024 · Link prediction in complex networks aims to estimate the likelihood that a link between two nodes is missing from the network. Links can be missing due to ...

7 days ago · To feed data into our deep learning model, snapshots from MD trajectories are converted into graphs representing the ligand binding structures. Each snapshot is ...

7 days ago · A comprehensive overview of a non-parametric probabilistic approach of model uncertainties for predictive models in structural dynamics. Article. Full-text ...

Aug 23, 2024 · This paper draws on this study to measure the degree of spatial distributional differences in the level of green manufacturing development in China, with ...