collaborators

6 papers

cs.CL2026

Fidelity-Diversity Metrics for Text

Amanda Wang, Tudor Manole, Florentina Bunea +1

As language modeling technology matures, there is an increasing research focus on the composition and curation of datasets used to train these models. For instance, practitioners c…

math.ST2026

Testing Imprecise Hypotheses

Lucas Kania, Tudor Manole, Larry Wasserman +1

Many scientific applications involve testing theories that are only partially specified. This task often amounts to testing the goodness-of-fit of a candidate distribution while al…

quant-ph2025

How much can we learn from quantum random circuit sampling?

Tudor Manole, Daniel K. Mark, Wenjie Gong +3

Benchmarking quantum devices is a foundational task for the sustained development of quantum technologies. However, accurate in situ characterization of large-scale quantum devices…

math.ST2025

Local Poisson Deconvolution for Discrete Signals

Shayan Hundrieser, Tudor Manole, Danila Litskevich +1

We analyze the statistical problem of recovering an atomic signal, modeled as a discrete uniform distribution , from a binned Poisson convolution model. This question is motiva…

math.ST2025

Statistical Inference for Optimal Transport Maps: Recent Advances and Perspectives

Sivaraman Balakrishnan, Tudor Manole, Larry Wasserman

In many applications of optimal transport (OT), the object of primary interest is the optimal transport map. This map rearranges mass from one probability distribution to another i…

math.ST2025

Stability Bounds for Smooth Optimal Transport Maps and their Statistical Implications

Sivaraman Balakrishnan, Tudor Manole

We study estimators of the optimal transport (OT) map between two probability distributions. We focus on plugin estimators derived from the OT map between estimates of the underlyi…