no code implementations • 30 Nov 2023 • Linfeng Du, Ji Xin, Alex Labach, Saba Zuberi, Maksims Volkovs, Rahul G. Krishnan
Transformer-based models have greatly pushed the boundaries of time series forecasting recently.
1 code implementation • 25 Apr 2023 • Alex Labach, Aslesha Pokhrel, Xiao Shi Huang, Saba Zuberi, Seung Eun Yi, Maksims Volkovs, Tomi Poutanen, Rahul G. Krishnan
Electronic health records (EHRs) recorded in hospital settings typically contain a wide range of numeric time series data that is characterized by high sparsity and irregular observations.
1 code implementation • 29 Jul 2021 • Kin Kwan Leung, Clayton Rooke, Jonathan Smith, Saba Zuberi, Maksims Volkovs
Time series data introduces two key challenges for explainability methods: firstly, observations of the same feature over subsequent time steps are not independent, and secondly, the same feature can have varying importance to model predictions over time.