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Constraint-Free Structure Learning with Smooth Acyclic Orientations
The structure learning problem consists of fitting data generated by a Directed Acyclic Graph (DAG) to correctly reconstruct its arcs.
Causal Abstraction with Soft Interventions
Causal abstraction provides a theory describing how several causal models can represent the same system at different levels of detail.
Ontology-Driven Semantic Alignment of Artificial Neurons and Visual Concepts
Semantic alignment methods attempt to establish a link between human-level concepts and the units of an artificial neural network.
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