7 citations · 11 across the 7 of their papers we have counts for
3 papers · 1 filter
Interpretable Model Drift Detection
Pranoy Panda, Kancheti Sai Srinivas, Vineeth N Balasubramanian +1
Data in the real world often has an evolving distribution. Thus, machine learning models trained on such data get outdated over time. This phenomenon is called model drift. Knowled…
Matching Learned Causal Effects of Neural Networks with Domain Priors
Sai Srinivas Kancheti, Abbavaram Gowtham Reddy, Vineeth N Balasubramanian +1
A trained neural network can be interpreted as a structural causal model (SCM) that provides the effect of changing input variables on the model's output. However, if training data…
Instance-wise Causal Feature Selection for Model Interpretation
Pranoy Panda, Sai Srinivas Kancheti, Vineeth N Balasubramanian
We formulate a causal extension to the recently introduced paradigm of instance-wise feature selection to explain black-box visual classifiers. Our method selects a subset of input…