8 papers
Generalization of Pearl's Front-Door Criterion
Carol Wu, Elina Robeva
Pearl's front-door criterion provides a set of sufficient conditions for estimating the total causal effect from observational data in the presence of latent confounding, using the…
Gradient-flow SDEs have unique transient population dynamics
Vincent Guan, Joseph Janssen, Nicolas Lanzetti +3
Identifying the drift and diffusion of an SDE from its population dynamics is a notoriously challenging task. Researchers in machine learning and single-cell biology have only been…
Identifying Drift, Diffusion, and Causal Structure from Temporal Snapshots
Vincent Guan, Joseph Janssen, Hossein Rahmani +4
Stochastic differential equations (SDEs) are a fundamental tool for modelling dynamic processes, including gene regulatory networks (GRNs), contaminant transport, financial markets…
Identifiability in Graphical Discrete Lyapunov Models
Cecilie Olesen Recke, Sarah Lumpp, Nataliia Kushnerchuk +4
In this paper, we study discrete Lyapunov models, which consist of steady-state distributions of first-order vector autoregressive models. The parameter matrix of such a model enco…
Algebraic geometry of rational neural networks
Alexandros Grosdos, Elina Robeva, Maksym Zubkov
We study the expressivity of rational neural networks (RationalNets) through the lens of algebraic geometry. We consider rational functions that arise from a given RationalNet to b…
Algebraic Constraints for Linear Acyclic Causal Models
Cole Gigliotti, Elina Robeva
In this paper we study the space of second- and third-order moment tensors of random vectors which satisfy a Linear Non-Gaussian Acyclic Model (LiNGAM). In such a causal model each…