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Anaconda: A Non-Adaptive Conditional Sampling Algorithm for Distribution Testing

Actively Avoiding Nonsense in Generative Models

INSPECTRE: Privately Estimating the Unseen

Robustly Learning a Gaussian: Getting Optimal Error, Efficiently

Testing Ising Models

Which Distribution Distances are Sublinearly Testable?

Concentration of Multilinear Functions of the Ising Model with Applications to Network Data

Being Robust (in High Dimensions) Can Be Practical

Priv'IT: Private and Sample Efficient Identity Testing

Robust Estimators in High Dimensions without the Computational Intractability