3 papers
econ.EM2026
Causal clustering: design of cluster experiments under network interference
Davide Viviano, Lihua Lei, Guido Imbens +3
This paper studies the design of cluster experiments to estimate the global treatment effect in the presence of network spillovers. We provide a framework to choose the clustering…
cs.LG2026
Flow Sampling: Learning to Sample from Unnormalized Densities via Denoising Conditional Processes
Aaron Havens, Brian Karrer, Neta Shaul
Sampling from unnormalized densities is analogous to the generative modeling problem, but the target distribution is defined by a known energy function instead of data samples. Bec…
stat.ME2025
Scalable Analysis of Bipartite Experiments
Liang Shi, Edvard Bakhitov, Kenneth Hung +4
Bipartite Experiments are randomized experiments where the treatment is applied to a set of units (randomization units) that is different from the units of analysis, and randomizat…