activation-function
There are 29 repositories under activation-function topic.
Jackpopc/aiLearnNotes
Artificial Intelligence Learning Notes.
kostas1515/AGLU
[ECCV2024 - Oral] Adaptive Parametric Activation
pouyaardehkhani/ActTensor
ActTensor: Activation Functions for TensorFlow. https://pypi.org/project/ActTensor-tf/ Authors: Pouya Ardehkhani, Pegah Ardehkhani
horrible-dong/DNRT
[ICLR 2024] Dynamic Neural Response Tuning
estija/Co-VeGAN
Co-VeGAN: Complex-Valued Generative Adversarial Network for Compressive Sensing MR Image Reconstruction
howion/activation-functions
Javascript implementation of some activation functions.
SensorOrgNet/Universal_Activation_Function
Source for the paper "Universal Activation Function for machine learning"
KhaledAshrafH/Logistic-Regression
This program implements logistic regression from scratch using the gradient descent algorithm in Python to predict whether customers will purchase a new car based on their age and salary.
mohit1997/PAF
Understanding DNN
MoinDalvs/Neural_Networks_From_Scratch
Neural_Networks_From_Scratch
xyproto/swish
:white_check_mark: Optimized Swish activation function, for neural networks
LaxmiChaudhary/SVHN-Deep-Neural-Network
Implementing an Image classification neural network to classify Street House View Numbers
luca-parisi/m_arcsinh
m-arcsinh: A Reliable and Efficient Function for Supervised Machine Learning (scikit-learn, TensorFlow, and Keras) and Feature Extraction (scikit-learn)
Adversarial-Intelligence-Group/flexnets
Hyper-Flexible Convolutional Neural Networks Based on Generalized Lehmer and Power Means
bhattbhavesh91/why-is-relu-non-linear
A small walk-through to show why ReLU is non linear!
pacocp/spocu-pytorch
:package: Non-official SPOCU activation function implementation for Pytorch and Tensorflow.
DalhousieAI/pytorch-logit-logic
Logit-space logical activation functions for pytorch
erikbuh/leaky_hardtanh
PyTorch implementation of the Leaky Hardtanh activation function
Xage0424/Comparative-Analysis-of-Activation-Functions-in-Shallow-Neural-Networks-for-Multi-Class-Image
Comparative Analysis of Activation Functions in Shallow Neural Networks for Multi-Class Image Classification Using MNIST Digits and CIFAR-10 Datasets with Fixed Architectural Parameters
akhileshravi/MultiLayerPerceptron
This is a repository for Multi-Layer Perceptron and Logistic Regression. There is a code (function) for Logistic Regression. SOme analysis is performed on the function. This is compared with the sklearn Logistic Regression function. Then, the decision boundary has also been plotted for the classification. The next part is the basic neural network. A class and a function has been created for this and it has been used for digit classification (mnist dataset).
priyadarshighosh/ANN_Everyday
Everything about Artificial Neural Network from Basic to Adavnced
rabieifk/CNN-with-CIFAR-10
Design of a CNN (Convolutional Neural Networks) to classify CIFAR-10 images
yangrussell/neural-networks
A feedforward multilayer perceptron with gradient descent & backpropagation written from scratch in Java
kuntala-c/Deep-Neural-Network-using-Cifar-10-dataset
Deep Learning concepts practice using Cifar-10 dataset
liuliuOD/Back-Propagation
Implement Back Propagation in deep neural network (DNN).
mbshbn/Intro-to-Artificial-Neural-Network
step by step tutorial for ANN
quantsareus/pytorch-learn-script-draft-for-designated-peer-reviewers-only
Pytorch Tutorial Introduction Learn Script PDF E-Book
RimTouny/Predictive-Analysis-for-Patient-Appointment-Attendance-in-a-Medical-Center-using-R
Predicting patient attendance at Bay Clinic using 'medicalcentre.csv'. Employing SVM, Decision Trees, and DNN models for accuracy, sensitivity, specificity evaluation, and ROC analysis. Part of a Data Science course in my master's program at the University of Ottawa 2023.