274 citations · 293 across the 10 of their papers we have counts for
3 papers · 2 filters
AutoMixer for Improved Multivariate Time-Series Forecasting on Business and IT Observability Data
Santosh Palaskar, Vijay Ekambaram, Arindam Jati +11
The efficiency of business processes relies on business key performance indicators (Biz-KPIs), that can be negatively impacted by IT failures. Business and IT Observability (BizITO…
TSMixer: Lightweight MLP-Mixer Model for Multivariate Time Series Forecasting
Vijay Ekambaram, Arindam Jati, Nam Nguyen +2
Transformers have gained popularity in time series forecasting for their ability to capture long-sequence interactions. However, their high memory and computing requirements pose a…
TsSHAP: Robust model agnostic feature-based explainability for time series forecasting
Vikas C. Raykar, Arindam Jati, Sumanta Mukherjee +4
A trustworthy machine learning model should be accurate as well as explainable. Understanding why a model makes a certain decision defines the notion of explainability. While vario…