activity
20192025
most citedTiny Time Mixers (TTMs): Fast Pre-trained Models for Enhanced Zero/Few-Shot Forecasting of Multivariate Time Series

11 citations · 16 across the 8 of their papers we have counts for

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Showing 2023Show all

2 papers · 1 filter

cs.LG2023

Semi-supervised counterfactual explanations

Shravan Kumar Sajja, Sumanta Mukherjee, Satyam Dwivedi

Counterfactual explanations for machine learning models are used to find minimal interventions to the feature values such that the model changes the prediction to a different outpu…

cs.LG2023★ 1 cited

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…