Search Results for author:
Found 2 papers, 1 papers with code
Learning Generative Models for Active Inference using Tensor Networks
The ability of tensor networks to represent the probabilistic nature of quantum states as well as to reduce large state spaces makes tensor networks a natural candidate for active inference.
A learning gap between neuroscience and reinforcement learning
Historically, artificial intelligence has drawn much inspiration from neuroscience to fuel advances in the field.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
