173 citations · 177 across the 4 of their papers we have counts for
4 papers
Hierarchically Coherent Multivariate Mixture Networks
Kin G. Olivares, David Luo, Cristian Challu +3
Large collections of time series data are often organized into hierarchies with different levels of aggregation; examples include product and geographical groupings. Probabilistic…
Debiased Contrastive Learning for Sequential Recommendation
Yuhao Yang, Chao Huang, Lianghao Xia +3
Current sequential recommender systems are proposed to tackle the dynamic user preference learning with various neural techniques, such as Transformer and Graph Neural Networks (GN…
HierarchicalForecast: A Reference Framework for Hierarchical Forecasting in Python
Kin G. Olivares, Azul Garza, David Luo +5
Large collections of time series data are commonly organized into structures with different levels of aggregation; examples include product and geographical groupings. It is often…
Taking Ethics, Fairness, and Bias Seriously in Machine Learning for Disaster Risk Management
Robert Soden, Dennis Wagenaar, Dave Luo +1
This paper highlights an important, if under-examined, set of questions about the deployment of machine learning technologies in the field of disaster risk management (DRM). While…