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Activation function

  • Training Autoencoders by Alternating Minimization

    Training Autoencoders by Alternating Minimization

  • CS 189 Introduction to Machine Learning Spring 2021 Jonathan Shewchuk HW6

    CS 189 Introduction to Machine Learning Spring 2021 Jonathan Shewchuk HW6

  • Can Temporal-Difference and Q-Learning Learn Representation? a Mean-Field Analysis

    Can Temporal-Difference and Q-Learning Learn Representation? a Mean-Field Analysis

  • Neural Networks Shuai Li John Hopcroft Center, Shanghai Jiao Tong University

    Neural Networks Shuai Li John Hopcroft Center, Shanghai Jiao Tong University

  • 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

  • A Deep Reinforcement Learning Neural Network Folding Proteins

    A Deep Reinforcement Learning Neural Network Folding Proteins

  • A Study of Activation Functions for Neural Networks Meenakshi Manavazhahan University of Arkansas, Fayetteville

    A Study of Activation Functions for Neural Networks Meenakshi Manavazhahan University of Arkansas, Fayetteville

  • Long Short-Term Memory 1 Introduction

    Long Short-Term Memory 1 Introduction

  • Chapter 02: Fundamentals of Neural Networks

    Chapter 02: Fundamentals of Neural Networks

  • 1 Activation Functions in Single Hidden Layer Feed

    1 Activation Functions in Single Hidden Layer Feed

  • Performance Evaluation of Word Embeddings for Sarcasm Detection- a Deep Learning Approach

    Performance Evaluation of Word Embeddings for Sarcasm Detection- a Deep Learning Approach

  • Deep Learning and Neural Networks

    Deep Learning and Neural Networks

  • Deep Learning and Reinforcement Learning

    Deep Learning and Reinforcement Learning

  • Neural Networks and Backpropagation

    Neural Networks and Backpropagation

  • Performance Analysis of Multilayer Perceptron in Profiling Side

    Performance Analysis of Multilayer Perceptron in Profiling Side

  • Perceptron 1 History of Artificial Neural Networks

    Perceptron 1 History of Artificial Neural Networks

  • Chapter 10: Artificial Neural Networks

    Chapter 10: Artificial Neural Networks

  • Multilayer Perceptrons

    Multilayer Perceptrons

Top View
  • Backpropagation
  • On the Impact of the Activation Function on Deep Neural Networks Training
  • Perceptrons and Neural Networks
  • Sigmoid-Weighted Linear Units for Neural Network Function
  • Perceptrons And
  • Introduction to Feedforward Neural Networks
  • Autoencoder-15-Mar-17.Pdf
  • Mish: a Self Regularized Non-Monotonic Activation Function
  • An Improvement Activation Function by Combining Sigmoid and Relu
  • SOTA Attention Mechanism and Activation Functions on Xlnet
  • Performance Analysis of Various Activation Functions Using LSTM Neural Network for Movie Recommendation Systems
  • Towards Learning Cross-Modal Perception-Trace Models
  • Revisit Long Short-Term Memory: an Optimization Perspective
  • Activation Functions in Neural Networks
  • 14.1 Autoencoders
  • Supervised Sequence Labelling with Recurrent Neural Networks
  • Backpropagation
  • A New Activation Function for Training Deep Neural Networks to Avoid Local Minimum


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