We are delighted to share our paper “Disentangled Representations for Causal Cognition” (arxiv.org/abs/2407.00744), the outcome of a long collaboration with Filippo Torresan.
The paper proposes a computational framework for causal cognition in natural and artificial agents, drawing from recent work in causal machine learning (in part based on recent developments of Markov categories in applied category theory) and reinforcement learning.
#causality #machinelearning #disentanglement #disentangled #representation #cognition #cognitivescience
