general deep neural network with L layers model built from scratch with python numpy. coded as a practice on Deep Learning Specialization first course by Andrew Ng. An educational Python project ...

Abstract: The provincial transportation carbon emissions (TCEs) in China exhibit spatiotemporal heterogeneous characteristics and have become increasingly unpredictable in recent years. To this end, ...

Eric Gutiérrez, 6th February 2026. A Python implementation of a 1-hidden layer neural network built entirely from first principles. This project avoids deep learning libraries (like TensorFlow or ...

This project explores the application of recursive neural networks (RNNs) in natural language processing, specifically for part-of-speech (POS) tagging. Drawing on foundational work by Socher et al.

These errors limit the accuracy of the final system. To overcome this limit, the researchers designed a "photonic multisynapse neural network" that processes information using light in a more direct ...

A team of astronomers led by Michael Janssen (Radboud University, The Netherlands) has trained a neural network with millions of synthetic black hole data sets. Based on the network and data from the ...

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: We explore the performance of various artificial neural network architectures, including a multilayer perceptron (MLP), Kolmogorov-Arnold network (KAN), LSTM-GRU hybrid recursive neural ...

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