Deep belief network (DBN)

Deep architecture with recurrent connections within layers, can learn compressed representations and retain stable attractors.

Neighborhood — ranked by edge-count

concept

Connectionism
implements
Central framework proposing intelligence resides in organization of relationships between components, not in individual parts; used to unify individual and collective intelligence.

cosine ≥ 0.65 · no typed edge

Entities in the same semantic neighborhood but without a typed relation to this one — candidates for new edges or unrecognized duplicates.

Deep Belief Networkframework0.910
Empathic Deep Q-Learning (DQN)framework0.778
Related technique that mitigates harmful behaviors by simulating another agent's perspective, but relies on hand-coded mechanisms
Generative Adversarial Network (GAN)method0.729
A self-supervised method where generator and discriminator compete; can lead to deceptive simulations.
Deep networks are biased toward finding simple fits to the data, and the bigger the model the stronger the bias, driving convergence to a smaller solution spacehypothesis0.729
Selective pressure toward convergence via implicit regularization
Deep Learningconcept0.728
Learning hierarchical representations of non-decomposable functions; proposed as formal equivalent to ETI process.
Neural Networksconcept0.725
Transformer Neural Networkframework0.715
Core machine learning architecture analyzed in the paper; shown to be mathematically related to TEM.
DeepMindinstitute0.712
Developed AlphaGo and AlphaCode.