15 papers
Sign Identifiability of Causal Effects in Stationary Stochastic Dynamical Systems
Gijs van Seeventer, Saber Salehkaleybar
We study identifiability in continuous-time linear stationary stochastic differential equations with a known causal structure. Unlike existing approaches, we relax the assumption o…
ACTIVA: Amortized Causal Effect Estimation via Transformer-based Variational Autoencoder
Andreas Sauter, Saber Salehkaleybar, Frank van Harmelen +2
Predicting post-intervention distributions from observational data is central to many scientific and decision-making problems, but remains challenging due to causal ambiguity, rest…
Inference Time Causal Probing in LLMs
Sadegh Khorasani, Saber Salehkaleybar, Negar Kiyavash +1
Causal probing methods aim to test and control how internal representations influence the behavior of generative models. In causal probing, an intervention modifies hidden states s…
Data-Driven Covariate Selection for Nonparametric and Cycle-Agnostic Causal Effect Estimation
Ana Leticia Garcez Vicente, Gijs van Seeventer, Saber Salehkaleybar
Estimating causal effects from observational data requires identifying valid adjustment sets. This task is especially challenging in realistic settings where latent confounding and…
Optimal Local Convergence Rates of Stochastic First-Order Methods under Local -PL
Saeed Masiha, Saber Salehkaleybar, Niao He +2
We study the local convergence rate of stochastic first-order methods under a local -Polyak-Lojasiewicz (-PL) condition in a neighborhood of a target connected component $\…
Near-Optimal Experiment Design in Linear non-Gaussian Cyclic Models
Ehsan Sharifian, Saber Salehkaleybar, Negar Kiyavash
We study the problem of causal structure learning from a combination of observational and interventional data generated by a linear non-Gaussian structural equation model that migh…