Publications

Learning Gaussian DAGs from Network Data

Optimizing Regularized Cholesky Score for Order-Based Learning of Bayesian Networks

Bayesian Causal Bandits with Backdoor Adjustment Prior

Structure Learning of Latent Factors via Clique Search on Correlation Thresholded Graphs

Learning Curves for Gaussian Process Regression with Power-Law Priors and Targets

Geometry of Linear Convolution Networks

Spectral Bias Outside the Training Set for Deep Networks in the Kernel Regime

On the Effectiveness of Persistent Homology

FoSR: First-Order Spectral Rewiring for Addressing Oversquashing In GNNs

Characterizing The Spectrum Of The NTK Via A Power Series Expansion