7 papers
Non-parametric recovery of causal diffusion mechanisms from steady-state observations
Richard Schwank, Mathias Drton
We consider sparse multivariate stochastic systems that evolve in continuous time according to a causal mechanism and present methodology to recover the system's time-infinitesimal…
Mapping the causal structure of price formation in Texas's transitioning electricity market
Shiva Madadkhani, Nils Sturma, Mathias Drton +1
Renewable deployment and rising demand from electrification and large digital loads are transforming electricity markets. However, how these developments reshape electricity price…
On the distance between mean and geometric median in high dimensions
Richard Schwank, Mathias Drton
The geometric median, a notion of center for multivariate distributions, has gained recent attention in robust statistics and machine learning. Although conceptually distinct from…
Matching Criterion for Identifiability in Sparse Factor Analysis
Nils Sturma, Miriam Kranzlmueller, Irem Portakal +1
Factor analysis models explain dependence among observed variables by a smaller number of unobserved factors. A main challenge in confirmatory factor analysis is determining whethe…
Trek-Based Parameter Identification for Linear Causal Models With Arbitrarily Structured Latent Variables
Nils Sturma, Mathias Drton
We develop a criterion to certify whether causal effects are identifiable in linear structural equation models with latent variables. Linear structural equation models correspond t…
Robust Score Matching
Richard Schwank, Andrew McCormack, Mathias Drton
Proposed in Hyvärinen (2005), score matching is a parameter estimation procedure that does not require computation of distributional normalizing constants. In this work we utilize…