Research topics in ML, AI and Deep Learning

A research overview lists key topics in machine learning, AI, and deep learning, including Euclidean geometry, group invariance theorem, universal approximation, player perceptron, curse of dimensionality, neocognitron, LeNet5, graph neural networks with chemical precursors and the Weisfeiler-Lehman test, DeepSets, CNN for translation symmetry, GNN for permutation symmetry, and 5G of GDL.

Euclidean Geometry Group Invariance Theorem Universal Approximation Player Perceptron Curse of Dimensionality neocognitron LeNet5 Graph Neural Network, Chemical Precursors, Weisteiler - Lehman test DeepSets CNN Symmetry translation, GNN Symmetry Permutation 5G of GDL