activation-functions
There are 204 repositories under activation-functions topic.
digantamisra98/Mish
Official Repository for "Mish: A Self Regularized Non-Monotonic Neural Activation Function" [BMVC 2020]
lucidrains/siren-pytorch
Pytorch implementation of SIREN - Implicit Neural Representations with Periodic Activation Function
harleyszhang/dl_note
深度学习系统笔记，包含深度学习数学基础知识、神经网络基础部件详解、深度学习炼丹策略、模型压缩算法详解。
KumapowerLIU/Rethinking-Inpainting-MEDFE
Rethinking Image Inpainting via a Mutual Encoder Decoder with Feature Equalizations. ECCV 2020 Oral
dalmia/siren
PyTorch implementation of Sinusodial Representation networks (SIREN)
Niranjankumar-c/DeepLearning-PadhAI
All the code files related to the deep learning course from PadhAI
Wongi-Choi1014/Korean-OCR-Model-Design-based-on-Keras-CNN
Korean OCR Model Design(한글 OCR 모델 설계)
densechen/AReLU
AReLU: Attention-based-Rectified-Linear-Unit
scart97/Siren-fastai2
Unofficial implementation of 'Implicit Neural Representations with Periodic Activation Functions'
AKASH2907/Introduction_to_Deep_Learning_Coursera
Intro to Deep Learning by National Research University Higher School of Economics
M-68/ActivationFunctions
Implementing activation functions from scratch in Tensorflow.
soumik12345/Pix2Pix
Image to Image Translation using Conditional GANs (Pix2Pix) implemented using Tensorflow 2.0
XAheli/Predicting-Indian-Stocks-Price-with-Stacked-LSTM
Predicting Indian stock prices using Stacked LSTM model. Analysing Reliance, Tata Steel, HDFC Bank, Infosys data. Data prep, EDA, hyperparameter tuning.
pouyaardehkhani/ActTensor
ActTensor: Activation Functions for TensorFlow. https://pypi.org/project/ActTensor-tf/ Authors: Pouya Ardehkhani, Pegah Ardehkhani
poopingface/sigmoidcolon
:poop: Sigmoid Colon: The biologically inspired activation function.
epishchik/TrainableActivation
Implementation for the article "Trainable Activations for Image Classification"
okozelsk/NET
Reservoir computing library for .NET. Enables ESN , LSM and hybrid RNNs using analog and spiking neurons working together.
ChristophReich1996/SmeLU
PyTorch reimplementation of the Smooth ReLU activation function proposed in the paper "Real World Large Scale Recommendation Systems Reproducibility and Smooth Activations" [arXiv 2022].
Rishit-dagli/GLU
An easy-to-use library for GLU (Gated Linear Units) and GLU variants in TensorFlow.
AaltoML/PeriodicBNN
Code for 'Periodic Activation Functions Induce Stationarity' (NeurIPS 2021)
MrGoriay/pwlu-pytorch
Unofficial pytorch implementation of Piecewise Linear Unit dynamic activation function
ThomasMrY/ActivationFunctionDemo
[TCAD 2018] Code for “Design Space Exploration of Neural Network Activation Function Circuits”
Ameobea/rnn-viz
Interactive visualizations and demos that are used in a blog post I wrote about logic in the context of neural networks
luca-parisi/quantum_relu
QReLU and m-QReLU: Two novel quantum activation functions for Deep Learning in TensorFlow, Keras, and PyTorch
shuuchen/frelu.pytorch
A PyTorch implementation of funnel activation https://arxiv.org/pdf/2007.11824.pdf
kumar-shridhar/ProbAct-Probabilistic-Activation-Function
Official PyTorch implementation of the paper : ProbAct: A Probabilistic Activation Function for Deep Neural Networks.
lucylow/salty-wet-man
Binary classification to filter and block unsolicited NSFW content from annoying coworkers... --- ...
NikolasMarkou/dl_techniques
Advanced deep learning learning techniques, layers, activations loss functions, all in keras / tensorflow
SensorOrgNet/Universal_Activation_Function
Source for the paper "Universal Activation Function for machine learning"
zohreazimi/Daily-Neural-Network-Exercise
My Daily Neural Network Exercise
mlpapers/neural-nets
Awesome papers on Neural Networks and Deep Learning
mohamedamine99/Visualizing-what-convnets-learn
This Github repository explains the impact of different activation functions on CNN's performance and provides visualizations of activations, convnet filters, and heatmaps of class activation for easier understanding of how CNN works.
ChristophReich1996/Pade-Activation-Unit
PyTorch reimplementation of the paper "Padé Activation Units: End-to-end Learning of Flexible Activation Functions in Deep Networks" [ICLR 2020].
ChristophReich1996/SmeLU-Triton
Triton reimplementation of the Smooth ReLU activation function proposed in the paper "Real World Large Scale Recommendation Systems Reproducibility and Smooth Activations" [arXiv 2022].
RahulBhalley/deep-learning-with-swift-for-tensorflow-book
Official source code for "Deep Learning with Swift for TensorFlow" 📖