There are 2 repositories under neural-network-architectures topic.
State of the Art of Music Generation with Deep Learning and AI
ActTensor: Activation Functions for TensorFlow. https://pypi.org/project/ActTensor-tf/ Authors: Pouya Ardehkhani, Pegah Ardehkhani
[arXiv'18] Security Analysis of Deep Neural Networks Operating in the Presence of Cache Side-Channel Attacks
Platform + GUI for hyperparameter optimization of recurrent neural networks (MATLAB).
:tv: A Python library for pruning and visualizing Keras Neural Networks' structure and weights
This repository is the implementation of several famous convolution neural network architecture with Keras. (Resnet v1, Resnet v2, Inception v1/GoogLeNet, Inception v2, Inception v3))
A toolkit for training CNN-1DRNN-CTC model to perform line-level Handwritten Text Recognition
Improving Prediction of Daily Visits of Wikipedia Mathematics Topics using Graph Neural Networks
Step by Step Math Behind Multilayer Perceptron Neural Networks Backpropagation with Manual Code Python and Excel For Detecting Potential Obesity
AI concepts, papers, algorithms, tutorials, AI roadmap
Public repository of our work in the search for an optimal multi-view crop classifier (considering encoder architectures and fusion strategies)
AAAI 2021. Neural Sequence-to-grid Module for Learning Symbolic Rules
A multi task neural network implemented from scratch, performing object detection with SSD and semantic segmentation with DeeplabV3+ simultaneosly!
Transformers-based Neural Network harbor logistic prediction model
The project implements Siamese Network with Triplet Loss in Keras to learn meaningful image representations in a lower-dimensional space. By training on the MNIST dataset, it creates a powerful architecture and implements Triplet Loss function. The resulting model enables applications like image search, recommendation systems, and image clustering.
High-fidelity artificial NoN (Network of Networks) generator
Many Neural Network architectures are there. Basically Keras applications. You can find here the structures, implementations all you need. Have fun!
Essential deep learning algorithms, concepts, examples and visualizations with TensorFlow. Popular and custom neural network architectures. Applications of neural networks.
Neural Network Architcture | ISI Kolkata
An Open Source Machine Learning Framework for Everyone
A small collection of basic neural networks for different tasks using pytorch.
My implementation for the labs of the Neural Networks and Deep Learning course that I studied at my university, Zewail City.
Participants in this Specialization have the opportunity to construct and train various neural network architectures, including Convolutional Neural Networks, Recurrent Neural Networks, LSTMs, and Transformers. They learn to enhance these networks with techniques such as Dropout, BatchNorm, Xavier/He initialization, among others.
Unofficial code with the paper "On the Role of Text Preprocessing in Neural Network Architectures" for IMDb dataset.
Programming Assignments completed under first Course of Deep Learning Specialisation(Coursera)
This project prove a simple gameplay system to understand Neural Network
Bottleneck ResNet16 Networks with Enhanced Architecture
Proyecto individual sobre los fundamentos matemáticos de las redes neuronales. Desarrollado durante los cursos propedéuticos de admisión a la Maestría en Ciencias de Datos de la Universidad de Sonora.
A Keras implementation of the ConvMixer architecture from the paper "Patches are all you need?", built from scratch using TensorFlow and Python.
A Keras implementation of the MobileViT architectures, built from scratch using TensorFlow and Python.
Tasks for Architecture of Neural Networks Course @ ITMO University
Tasks for Architecture of Neural Networks Course at ITMO University
An exploration of neural network architecture using regression in R.
Contains solutions and notes for the Deep Learning Specialization by Deeplearning.ai, Andrew Ng on Coursera
Custom ResNet18 Networks with Improved Architecture