activation-functions

Official Repsoitory for "Mish: A Self Regularized Non-Monotonic Neural Activation Function" [BMVC 2020]

Rethinking Image Inpainting via a Mutual Encoder Decoder with Feature Equalizations. ECCV 2020 Oral

PyTorch implementation of Sinusodial Representation networks (SIREN)

Pytorch implementation of SIREN - Implicit Neural Representations with Periodic Activation Function

All the code files related to the deep learning course from PadhAI

AReLU: Attention-based-Rectified-Linear-Unit

Unofficial implementation of 'Implicit Neural Representations with Periodic Activation Functions'

Implementing activation functions from scratch in Tensorflow.

Intro to Deep Learning by National Research University Higher School of Economics

Image to Image Translation using Conditional GANs (Pix2Pix) implemented using Tensorflow 2.0

Reservoir computing library for .NET. Enables ESN , LSM and hybrid RNNs using analog and spiking neurons working together.

A PyTorch implementation of funnel activation https://arxiv.org/pdf/2007.11824.pdf

The "Activation Function Demo" is a demo for implementing activation function with the mathod propsed in paper: Design Space Exploration of Neural Network Activation Function Circuits

Official PyTorch implementation of the paper : ProbAct: A Probabilistic Activation Function for Deep Neural Networks.

Online binary classification content control to filter and flag for inappropriate NSFW content

Korean OCR Model Design(한글 OCR 모델 설계)

Multilayer neural network framework implementation, used for classification and regression task. Can use multiple activation functions with backpropagation based on autograd library. Contains polynomial activation function for regression task.

**DeepLearning** Intro.. Need to wrap up more projects here...

3D visualization of common activation functions

Avoiding the vanishing gradients problem by adding random noise and batch normalization

BSc Thesis at FER-2019/20 led by doc. dr. sc. Marko Čupić

Awesome papers on Neural Networks and Deep Learning

This is a Keras implementation of the paper "LiSHT: Non-Parametric Linearly Scaled Hyperbolic Tangent Activation Function for Neural Networks" - https://arxiv.org/abs/1901.05894

⚡ Activation functions for neural networks

Email Systems Account Propagation & Services REST API + Open PGP

Robustness of Deep Neural Networks using Trainable Activation Functions

Simple Tutorial to Explain the Pros and Cons of Sigmoid Activation Function

A small walk-through to show why ReLU is non linear!

Corruption Robust Image Classification with a new Activation Function. Our proposed Activation Function is inspired by the Human Visual System and a classic signal processing fix for data corruption.