Dr. James McCaffrey presents a complete end-to-end demonstration of decision tree regression from scratch using the C# language. The goal of decision tree regression is to predict a single numeric ...
This project contains implementations of simple neural network models, including training scripts for PyTorch and Lightning frameworks. The goal is to provide a modular, easy-to-understand codebase ...
In this video, we will see What is Activation Function in Neural network, types of Activation function in Neural Network, why to use an Activation Function and which Activation function to use. The ...
The demo runs entirely in your browser (no backend required) and shows an animated XOR training visualization.
Deep learning is revolutionizing Neuroscience and Healthcare. One driver for this change is the exponential growth in the volume of biomedical data generated by modern medical imaging technology and ...
ABSTRACT: We explore the performance of various artificial neural network architectures, including a multilayer perceptron (MLP), Kolmogorov-Arnold network (KAN), LSTM-GRU hybrid recursive neural ...
Abstract: This work addresses the problem of recursive state estimation for networked control systems with unknown nonlinearities and binary-encoding mechanisms (BEMs). To enhance transmission ...
Neural Ordinary Differential Equations are significant in scientific modeling and time-series analysis where data changes every other moment. This neural network-inspired framework models ...
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