1 citations · 1 across the 4 of their papers we have counts for
4 papers
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…
Metrics Over Merit: The Hidden Costs of Citation Impact in Research
Vugar Ismailov
Once upon a time, scientists' worth was measured by their ideas, proofs, and perhaps how eloquently they debated Hilbert's problems at seminars. But now, citation metrics have come…
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…
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…