3 papers
cs.LG2026
Max-Min Neural Network Operators For Approximation of Multivariate Functions
Abhishek Yadav, Uaday Singh, Feng Dai
In this paper, we develop a multivariate framework for approximation by max-min neural network operators. Building on the recent advances in approximation theory by neural network…
cs.LG2026
Kantorovich-Type Stochastic Neural Network Operators for the Mean-Square Approximation of Certain Second-Order Stochastic Processes
Sachin Saini, Uaday Singh
Artificial neural network operators (ANNOs) have been widely used for approximating deterministic input-output functions; however, their extension to random dynamics remains compar…
stat.ML2025
Constructive Approximation of Random Process via Stochastic Interpolation Neural Network Operators
Sachin Saini, Uaday Singh
In this paper, we construct a class of stochastic interpolation neural network operators (SINNOs) with random coefficients activated by sigmoidal functions. We establish their boun…