TensorCast: forecasting and mining with coupled tensors

By Miguel Ramos de Araujo, Pedro Manuel Pinto Ribeiro, Hyun Ah Song, Christos Faloutsos. 2018

10 citations recorded by the source corpus.

Subfields: Computational Mathematics, Statistical and Nonlinear Physics, Transportation

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computational Mathematics

1. Lijun Sun
2. Xinyu Chen
3. Alex Smola

In Statistical and Nonlinear Physics

1. Dean Phillips Foster
2. Lijun Sun
3. Xinyu Chen
4. Alex Smola
5. Bernie Wang
6. Arthur Gretton
7. Kenji Fukumizu
8. Le Song

In Transportation

1. Lijun Sun
2. Xinyu Chen

Citations in the corpus

• Deep Factors for Forecasting (2019, methodology): “Closely related are the matrix factorization (MF) techniques (Yu et al., 2016; Xie et al., 2017; Hooi et al., 2019) and tensor factorization (Araujo et al., 2019), which have been applied to the time series matrix with temporal regularization to ensure the regularity of the latent time series.”
• Bayesian Temporal Factorization for Multidimensional Time Series Prediction (2019, methodology): “…modeling multivariate and multidimensional time series data, several notable approaches have been proposed recently based on ma-a trix/tensor factorization (see [1] for a brief review and e.g., [11], [12], [13], [14], [15], [16], [17], [18], [19], [20], [21], [22] for some representative models).”