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cs.LG2026
Universal Approximation Theorem for Input-Connected Multilayer Perceptrons
Vugar Ismailov
We present the Input-Connected Multilayer Perceptron (IC-MLP), a feedforward neural network architecture in which each hidden neuron receives, in addition to the outputs of the pre…
cs.LG2025
On shallow feedforward neural networks with inputs from a topological space
Vugar Ismailov
We study feedforward neural networks with inputs from a topological space (TFNNs). We prove a universal approximation theorem for shallow TFNNs, which demonstrates their capacity t…
cs.LG2024
Universal approximation theorem for neural networks with inputs from a topological vector space
Vugar Ismailov
We study feedforward neural networks with inputs from a topological vector space (TVS-FNNs). Unlike traditional feedforward neural networks, TVS-FNNs can process a broader range of…