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Sigmoid function

  • Training Autoencoders by Alternating Minimization

    Training Autoencoders by Alternating Minimization

  • Neural Network in Hardware

    Neural Network in Hardware

  • Population Dynamics: Variance and the Sigmoid Activation Function ⁎ André C

    Population Dynamics: Variance and the Sigmoid Activation Function ⁎ André C

  • Dynamic Modification of Activation Function Using the Backpropagation Algorithm in the Artificial Neural Networks

    Dynamic Modification of Activation Function Using the Backpropagation Algorithm in the Artificial Neural Networks

  • Two-Steps Implementation of Sigmoid Function for Artificial Neural Network in Field Programmable Gate Array

    Two-Steps Implementation of Sigmoid Function for Artificial Neural Network in Field Programmable Gate Array

  • Information Flows of Diverse Autoencoders

    Information Flows of Diverse Autoencoders

  • Compositional Distributional Semantics with Long Short Term Memory

    Compositional Distributional Semantics with Long Short Term Memory

  • Long Short-Term Memory 1 Introduction

    Long Short-Term Memory 1 Introduction

  • Neural Networks

    Neural Networks

  • 1 Activation Functions in Single Hidden Layer Feed

    1 Activation Functions in Single Hidden Layer Feed

  • Rethinking the Role of Activation Functions in Deep Convolutional Neural Networks for Image Classification

    Rethinking the Role of Activation Functions in Deep Convolutional Neural Networks for Image Classification

  • Chapter 10: Artificial Neural Networks

    Chapter 10: Artificial Neural Networks

  • On the Derivatives of the Sigmoid

    On the Derivatives of the Sigmoid

  • Applied Machine Learning

    Applied Machine Learning

  • Long Short-Term Memory Recurrent Neural Network Architectures for Generating Music and Japanese Lyrics

    Long Short-Term Memory Recurrent Neural Network Architectures for Generating Music and Japanese Lyrics

  • Backpropagation

    Backpropagation

  • Chapter 6 Convolutional Neural Network

    Chapter 6 Convolutional Neural Network

  • Perceptrons and Neural Networks

    Perceptrons and Neural Networks

Top View
  • An Improvement Activation Function by Combining Sigmoid and Relu
  • Performance Analysis of Various Activation Functions Using LSTM Neural Network for Movie Recommendation Systems
  • CPSC 340: Data Mining Machine Learning
  • Revisit Long Short-Term Memory: an Optimization Perspective
  • CS 224D: Assignment #1
  • Backpropagation
  • A New Activation Function for Training Deep Neural Networks to Avoid Local Minimum
  • Understanding LSTM – a Tutorial Into Long Short-Term Memory Recurrent Neural Networks
  • On Some Properties of the Sigmoid Function Kwara Nantomah
  • Activation Functions: Comparison of Trends in Practice and Research for Deep Learning
  • Review and Comparison of Commonly Used Activation Functions for Deep Neural Networks
  • Introduction to Deep Learning & Neural Networks
  • Weighted Sigmoid Gate Unit for an Activation Function of Deep Neural Network Masayuki Tanaka, Member, IEEE
  • Implementation of Efficient Multilayer Perceptron ANN Neurons on Field Programmable Gate Array Chip Emmanuel ADETIBA*1, F.A
  • Word2vec Embeddings: CBOW and Skipgram
  • Implementation of a New Sigmoid Function in Backpropagation Neural Networks
  • A Set of Useful Equalities About the Exponential and the Sigmoid
  • Efficient Evaluation of Activation Functions Over Encrypted Data


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