Publications

CausalDS is a benchmark generator for agentic causal data science: every problem is generated fresh in its entirety, with tasks spanning all three rungs of Pearl’s hierarchy that involve significant tool use. Exam composition is a free parameter: it can be tailored to a specific goal or grounded in real-world corpora. The benchmark jointly tests symbolic causal reasoning, data-science execution, uncertainty quantification, epistemic abstention, and coding/tool use.

The classical Tweedie’s formula connects the score under Gaussian noise to the posterior mean. We generalize this result to the Energy-Tweedie identity: the score from a wider family of noising distributions is connected to a path-derivative of a matched energy score. Among other things, this opens new routes to score estimation, noise parameter estimation, and provides the score-based perspective on diffusion approaches based on scoring rules.

For the Distributional Principal Autoencoder (DPA), we prove an exact identity linking the geometry of the learned encoding to the score of the data distribution, and show that any latent coordinates beyond the data manifold dimension become completely uninformative. This means that the DPA learns nonlinear manifolds shaped locally by the data density, with a clear, testable dimensionality criterion — conditional independence, giving it a natural nonlinear-PCA interpretation.

We propose a novel methodology - Causal Disentanglement with Extreme Values (CDEV) - to identify representations learned by GANs. When trained on raw whale communication, it finds - for the first time - specific acoustic attributes that might serve as carriers of meaning.

Modeling the translation and review processes as zero-inflated fat-tailed distributions, we show how to extract useful information on translators’ reliability with as little as one review per translation.

By solving for the time-dependent effect of a voltage probe on the current through a quantum dot, we demonstrate that one can controllably observe the transition between the quantum and classical electric conductance.