Abstract: Code translation between programming languages is a complex task that poses significant challenges in maintaining both the structure and functionality of the translated code. This work ...

Abstract: This article proposes a neural network (NN)-based calibration framework via quantization code reconstruction to address the critical limitation of multidimensional NNs (MDNNs) in ...

A comprehensive implementation of a Variational Autoencoder (VAE) for unsupervised data generation with uncertainty quantification, featuring comparative analysis against deterministic baselines. This ...

Reliable estimation of Chlorophyll-a concentration (Chl-a) from remotely sensed data is essential for monitoring the health of aquatic ecosystems and supporting environmental policy decisions (El ...

We will create a Deep Neural Network python from scratch. We are not going to use Tensorflow or any built-in model to write the code, but it's entirely from scratch in python. We will code Deep Neural ...

The Boryviter Center of Research is developing a neural network for the passive collection and analysis of publications in enemy media resources. Pavlo Musienko, head of the analytical department, ...

Institute of Physics, Faculty of Physics, Astronomy and Informatics, Nicolaus Copernicus University, Grudziądzka 5, 87-100 Toruń, Poland ...

With increasing model complexity, models are typically re-used and evolved rather than starting from scratch. There is also a growing challenge in ensuring that these models can seamlessly work across ...