ANN Architectures are composed of multiple ANN Layers Auto-Regression／Regressor／Regressive (AR) Model Autoencoders (AE) Capsule Networks Convolutional Kolmogorov-Arnold Networks (Convolutional KAN) Convolutional Neural Networks (CNN) - Translation／Translational／Shift Equivariant／Equivariance／Invariant／Invariance CNN Dense Networks (Dense Net) Diffusion Model - Diffusion Probabilistic Model - Score-Based Generative Model Encoder-Decoder Model Fast R-CNN Faster R-CNN Flow-Based Generative Model Fully Convolutional Networks (FCN) Gated Recurrent Neural Networks (Gated RNN) Gauge-Equivariant Convolutional Neural Networks (CNN) Generative Adversarial Networks (GAN) Graph Neural Networks (GNN) Group Equivariant Convolutional Neural Networks (G-CNN) Joint Embedding Predictive Architecture (JEPA) Kolmogorov-Arnold Networks (KAN) Liquid Neural Networks (LNN) Neocognitron Neural Turing Machines (NTM) Pulse-Coupled Neural Networks (PCNN) Radial Basis Function (RBF) Networks Recurrent Neural Networks (RNN) Region-based Convolutional Neural Network (R-CNN) Shuffle Networks Spiking Neural Networks (SNN) Squeeze-and-Excitation Networks (SENets) Switching Neural Networks (SNN) Temporal Convolutional Networks (TCN) Transformer Neural Networks (TNN) - Transformers Vanilla／Feed-Forward Neural Networks (FNN／FFNN／FFN) - Multi-Layer／Multilayer Perceptrons (MLP) You Only Look Once (YOLO)
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