TensorFlow-based neural network library machine-learningdeep-learningtensorflowartificial-intelligenceneural-networks UpdatedFeb 14, 2025 Python Load more… Improve this page Add a description, image, and links to theneural-networkstopic page so that developers can more easily learn about it. ...
Python Simple PyTorch Implementation of Physics Informed Neural Network (PINN) machine-learningpytorchphysics-informed-neural-networks UpdatedJul 5, 2024 Jupyter Notebook idrl-lab/idrlnet Star220 Code Issues Pull requests Discussions IDRLnet, a Python toolbox for modeling and solving problems through ...
Python Getting Started Citing Releases and Contributing General DyNet is a neural network library developed by Carnegie Mellon University and many others. It is written in C++ (with bindings in Python) and is designed to be efficient when run on either CPU or GPU, and to work well with netwo...
batch_size=128tells Keras to use 128 training samples at a time to train the network. Larger batch sizes speed the training time (fewer passes are required in each epoch to consume all of the training data), but smaller batch sizes sometimes increase accuracy. Once you've com...
Our task consisted of reconstructing these image portions using a single- or multilayer fully-connected linear neural network. To ensure no architectural bottleneck exists, the internal (hidden) dimension of the multilayer network remained at 322, the same as the input and output. The initial parame...
Electrical conductivity measurements were performed using a Keithley 2400 sourcemeter in two-point configuration. The samples measured consisted of EGNITE films of 1 × 1 cm2 on top of a SiO2 substrate. Data analysis X-ray diffraction, Raman and XPS data were analysed using Python 3.7 packa...
The model employed to generate this caption is composed by two different networks. First, one is a convolutional neural network to extract a set of feature vectors referred to as annotation vectors. The second part of the model is a long short-term memory (LSTM) netw...
Network architecture The input to the model is a square grayscale image of the rat, as produced by the rat tracking module. The output consists of three pairs of Cartesian coordinates, representing the three points of nose, neck, and the base of the tail on the rat image. The model is ...
Neural Network Distiller by Intel AI Lab: a Python package for neural network compression research. https://nervanasystems.github.io/distiller - wsxwd/distiller
Hands-On Graph Neural Networks Using Python Useful Repos o GitHub Edge-GNN: implementation of EGNN(C)-M (GCN without multi-dimensional edge features) https://github.com/vietph34/Edge_GNN This is the code repository for Hands-On Graph Neural Networks Using Python, published by Packt. Pract...