6 papers
Topology-Informed Neural Networks for Flood Detection in Optical and Synthetic Aperture Radar Imagery
Sophia Li, Max Zhao, Raghu G. Raj +1
Floods frequently impact regions around the world. Rapid and accurate flood detection is crucial for emergency response and timely mitigation of human and economic loss. The expand…
Conformal C2ST: Turning weak classifiers into strong two-sample tests
Vansh Bansal, Tianyu Chen, James G. Scott
The two-sample testing problem, a fundamental task in statistics and machine learning, seeks to determine whether two sets of samples, drawn from underlying distributions and $…
A Dynamic Mode Decomposition Approach to Morphological Component Analysis
Owen T. Huber, Raghu G. Raj, Tianyu Chen +1
This paper introduces a novel methodology of adapting the representation of videos based on the dynamics of their scene content variation. In particular, we demonstrate how the clu…
CoLT: The conditional localization test for assessing the accuracy of neural posterior estimates
Tianyu Chen, Vansh Bansal, James G. Scott
We consider the problem of validating whether a neural posterior estimate \( q(θ\mid x) \) is an accurate approximation to the true, unknown true posterior \( p(θ\mid x) \). Exis…
Conditional diffusions for amortized neural posterior estimation
Tianyu Chen, Vansh Bansal, James G. Scott
Neural posterior estimation (NPE), a simulation-based computational approach for Bayesian inference, has shown great success in approximating complex posterior distributions. Exist…
Identifying General Mechanism Shifts in Linear Causal Representations
Tianyu Chen, Kevin Bello, Francesco Locatello +2
We consider the linear causal representation learning setting where we observe a linear mixing of unknown latent factors, which follow a linear structural causal model. Recent…