activation-function

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.

aluminarius/ReLU_Plus_Plus

ReLU++: A modified ReLU activation function with enhanced performance for deep learning models.

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

ewdlop/ComputingNeuralNetworksNote

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

mr-ravin/aptx_activation

This repository offers a Python Package for the PyTorch implementation of the APTx activation function, as introduced in the paper "APTx: Better Activation Function than MISH, SWISH, and ReLU's Variants used in Deep Learning".

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.