Targeted Reduction of Causal Models
Why does a phenomenon occur? Addressing this question is central to most scientific inquiries based on empirical observations, and …
Learning soft interventions in complex equilibrium systems
Complex systems often contain feedback loops that can be described as cyclic causal models. Intervening in such systems may lead to …
Uncovering the organization of neural circuits with Generalized Phase Locking Analysis
Modern neural recording techniques give access to increasingly highly multivariate spike data, together with spatio-temporal activities …
Independent Mechanism Analysis, a New Concept?
Independent component analysis provides a principled framework for unsupervised representation learning, with solid theory on the …
Self-Supervised Learning with Data Augmentations Provably Isolates Content from Style
Self-supervised representation learning has shown remarkable success in a number of domains. A common practice is to perform data …
Coupling of hippocampal theta and ripples with pontogeniculooccipital waves
The hippocampus has a major role in encoding and consolidating long-term memories, and undergoes plastic changes during sleep1. These …
A theory of independent mechanisms for extrapolation in generative models
Generative models can be trained to emulate complex empirical data, but are they useful to make predictions in the context of …
Groupe invariance principles for causal generative models
The postulate of independence of cause and mechanism (ICM) has recently led to several new causal discovery algorithms. The …
Shifts of Gamma Phase Reflect Dynamic Information Transfer
We investigate how oscillations of cortical activity in the gamma frequency range (50–80 Hz) may influence dynamically the direction …
