GitHub

SaeedRahmani/DCRNN_PyTorch_Saeed

Here is an article about Using HDF5 with Python. Run the following commands to generate train/test/val dataset at data/{METR-LA,PEMS-BAY}/{train,val,test}.npz. As the ...
IEEE

Parametric Fault Diagnosis Using Transfer Cerebellar Model Neural Network for Power Electronic Converter

Abstract: The intelligent fault diagnosis methods have become increasingly popular in the field of power electronic converters fault diagnosis. However, in industrial applications, only a small amount ...
Hosted on MSN

Network in Network (NiN) Deep Neural Network Explained with PyTorch

Learn how Network in Network (NiN) architectures work and how to implement them using PyTorch. This tutorial covers the concept, benefits, and step-by-step coding examples to help you build better ...
marktechpost

A Step by Step Guide to Solve 1D Burgers’ Equation with Physics-Informed Neural Networks (PINNs): A PyTorch Approach Using Automatic Differentiation and Collocation Methods

First, we install the PyTorch and matplotlib libraries using pip, ensuring you have the necessary tools for building neural networks and visualizing the results in your Google Colab environment. Copy ...
Scientific Research Publishing

Thammano, A. and Meengen, A. (2005) A New Evolutionary Neural Network Classifier. Advances in Knowledge Discovery and Data Mining, Hanoi, 18-20 May 2005, 249-255.

ABSTRACT: The early detection of type 2 diabetes is a major challenge for healthcare professionals, as a late diagnosis can lead to severe and difficult-to-manage complications. In this context, this ...
IEEE

On-Chip Implementation of Neural Network-Based Classifier Models for E-Nose With Chemometric Analysis

Abstract: The present work focuses on the comprehensive implementation of gas/mixture identification employing chemometric analysis followed by on-chip realization. The chemometric analysis has been ...
C&EN

TorchANI: A Free and Open Source PyTorch-Based Deep Learning Implementation of the ANI Neural Network Potentials

This paper presents TorchANI, a PyTorch-based program for training/inference of ANI (ANAKIN-ME) deep learning models to obtain potential energy surfaces and other physical properties of molecular ...