1 citations · 1 across the 4 of their papers we have counts for
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Reconciling Causality and Non-Equilibrium Thermodynamics with Hamiltonian Causal Models
Dario Rancati, Max Welling, Francesco Locatello
Causal modeling of physical temporal phenomena must handle interventions that act along trajectories, nonstationary induced laws, path-dependent effects, and feedback mediated by d…
Learning Discrete Diffusion of Graphs via Free-Energy Gradient Flows
Dario Rancati, Jan Maas, Francesco Locatello
Diffusion-based models on continuous spaces have seen substantial recent progress through the mathematical framework of gradient flows, leveraging the Wasserstein-2 () metri…
Unifying Causal Representation Learning with the Invariance Principle
Dingling Yao, Dario Rancati, Riccardo Cadei +2
Causal representation learning (CRL) aims at recovering latent causal variables from high-dimensional observations to solve causal downstream tasks, such as predicting the effect o…