181 citations · 184 across the 10 of their papers we have counts for
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Incorporating Interventional Independence Improves Robustness against Interventional Distribution Shift
Gautam Sreekumar, Vishnu Naresh Boddeti
We study the problem of learning robust discriminative representations of causally related latent variables given the underlying causal graph and a training set comprising passivel…
CoInD: Enabling Logical Compositions in Diffusion Models
Sachit Gaudi, Gautam Sreekumar, Vishnu Boddeti
How can we learn generative models to sample data with arbitrary logical compositions of statistically independent attributes? The prevailing solution is to sample from distributio…
Compositional World Knowledge leads to High Utility Synthetic data
Sachit Gaudi, Gautam Sreekumar, Vishnu Boddeti
Machine learning systems struggle with robustness, under subpopulation shifts. This problem becomes especially pronounced in scenarios where only a subset of attribute combinations…
Spurious Correlations and Where to Find Them
Gautam Sreekumar, Vishnu Naresh Boddeti
Spurious correlations occur when a model learns unreliable features from the data and are a well-known drawback of data-driven learning. Although there are several algorithms propo…
Physics Informed Neural Network for Dynamic Stress Prediction
Hamed Bolandi, Gautam Sreekumar, Xuyang Li +2
Structural failures are often caused by catastrophic events such as earthquakes and winds. As a result, it is crucial to predict dynamic stress distributions during highly disrupti…