4 citations · 8 across the 3 of their papers we have counts for
3 papers
cs.LG2023★ 4 cited
Time Interpret: a Unified Model Interpretability Library for Time Series
Joseph Enguehard
We introduce $\texttt{time_interpret}$, a library designed as an extension of Captum, with a specific focus on temporal data. As such, this library implements several feature attri…
cs.LG2023★ 1 cited
Learning Perturbations to Explain Time Series Predictions
Joseph Enguehard
Explaining predictions based on multivariate time series data carries the additional difficulty of handling not only multiple features, but also time dependencies. It matters not o…
cs.CL2023★ 3 cited
Sequential Integrated Gradients: a simple but effective method for explaining language models
Joseph Enguehard
Several explanation methods such as Integrated Gradients (IG) can be characterised as path-based methods, as they rely on a straight line between the data and an uninformative base…