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Found 8 papers, 4 papers with code
ChronosX: Adapting Pretrained Time Series Models with Exogenous Variables
Covariates provide valuable information on external factors that influence time series and are critical in many real-world time series forecasting tasks.
Chronos: Learning the Language of Time Series
We introduce Chronos, a simple yet effective framework for pretrained probabilistic time series models.
Generalized Matrix Means for Semi-Supervised Learning with Multilayer Graphs
We study the task of semi-supervised learning on multilayer graphs by taking into account both labeled and unlabeled observations together with the information encoded by each individual graph layer.
Spectral Clustering of Signed Graphs via Matrix Power Means
Moreover, we prove that the eigenvalues and eigenvector of the signed power mean Laplacian concentrate around their expectation under reasonable conditions in the general Stochastic Block Model.
Node Classification for Signed Social Networks Using Diffuse Interface Methods
Signed networks contain both positive and negative kinds of interactions like friendship and enmity.
The Power Mean Laplacian for Multilayer Graph Clustering
Multilayer graphs encode different kind of interactions between the same set of entities.
Community detection in networks via nonlinear modularity eigenvectors
In this work we propose a nonlinear relaxation which is instead based on the spectrum of a nonlinear modularity operator $\mathcal M$.
Clustering Signed Networks with the Geometric Mean of Laplacians
As a solution we propose to use the geometric mean of the Laplacians of positive and negative part and show that it outperforms the existing approaches.
