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Search results for neural gradient
gradient
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neural
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78 search results found
Deeplearning_ai_books
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14,417
deeplearning.ai(吴恩达老师的深度学习课程笔记及资源)
Innvestigate
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1,175
A toolbox to iNNvestigate neural networks' predictions!
Deeplearning.ai Solutions
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756
Solutions of assignments and translation to Chinese
Toy Neural Network Js
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407
Neural Network JavaScript library for Coding Train tutorials
Dnc
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386
Simple RNN, LSTM and Differentiable Neural Computer in pure Numpy
Ai Simplest Network
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317
The simplest form of an artificial neural network explained and demonstrated.
Python Neural Network
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278
This is an efficient implementation of a fully connected neural network in NumPy. The network can be trained by a variety of learning algorithms: backpropagation, resilient backpropagation and scaled conjugate gradient learning. The network has been developed with PYPY in mind.
Deepneuralclassifier
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243
Deep neural network using rectified linear units to classify hand written symbols from the MNIST dataset.
Spytorch
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218
Tutorial for surrogate gradient learning in spiking neural networks
Invertinggradients
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109
Algorithms to recover input data from their gradient signal through a neural network
Deep Learning
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107
personal practice(个人练习,实现了深度学习中的一些算法,包括:四种初始化方法(zero initialize, random initialize, xavier initialize, he initialize),深度神经网络,正则化,dropout, 三种梯度下降方法(BGD, SGD, mini-batch),六种优化算法(momentum、nesterov momentum、Adagrad、Adadelta、RMSprop、Adam),梯度检验、batch normalization)、RNN
Scorch
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104
scorch is a deep learning framework in Scala inspired by PyTorch
Dni.pytorch
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102
Implement Decoupled Neural Interfaces using Synthetic Gradients in Pytorch
Deep Learning Specialization Coursera
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92
Deep Learning Specialization courses by Andrew Ng, deeplearning.ai
Asng Nas
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79
Adaptive Stochastic Natural Gradient Method for One-Shot Neural Architecture Search
Gran Dag
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74
Anode
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72
Nas With Code
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72
Neural Architecture Search (NAS) papers with code
Eunn Tensorflow
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62
Efficient Unitary Neural Network(EUNN) implementation in Tensorflow
Pathnet Pytorch
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60
PyTorch implementation of PathNet: Evolution Channels Gradient Descent in Super Neural Networks
Autodiff
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58
Rudimentary automatic differentiation framework
Gradientpathologiespinns
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52
Diffgrad
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51
diffGrad: An Optimization Method for Convolutional Neural Networks
Clever
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46
CLEVER (Cross-Lipschitz Extreme Value for nEtwork Robustness) is a robustness metric for deep neural networks
Ntk
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43
Code for experiments in my blog post on the Neural Tangent Kernel: https://rajatvd.github.io/NTK
Artificial Neural Networks With Jupyter
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41
Artificial Neural Networks - Gradient descent, BFGS, Regularization with Jupyter notebook
Sgrnn
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39
Tensorflow implementation of Synthetic Gradient for RNN (LSTM)
Neural Net
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35
An educational neural net library in Rust
Vinn
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34
ViNN - an OpenCL accelerated neural networks library
Convolutional Neural Network Compression Survey
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32
Adversarial Robustness Public
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30
Code for AAAI 2018 accepted paper: "Improving the Adversarial Robustness and Interpretability of Deep Neural Networks by Regularizing their Input Gradients"
Dni Tensorflow
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30
DNI (Decoupled Neural Interfaces using Synthetic Gradients) Implementation with Tensorflow.
Ntk
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26
NTK reading group
Gradient_starvation
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24
Gradient Starvation: A Learning Proclivity in Neural Networks
Only_numpy_basic
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23
This repository contains code for my only numpy basic.
Gone
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23
neural network library in go from scratch
Minimalistic Multiple Layer Neural Network From Scratch In Python
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21
Minimalistic Multiple Layer Neural Network from Scratch in Python.
Newbie_neural_network_practice
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21
适合新手学习的神经网络实践教程+代码。a awesome neural network practice project for newbie.我的CSDN博客:
Nnnamedentity
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21
Named Entity Recognition (NER) models (neural and sparse) implemented based on package LibN3L
Admm Neuralnetworks
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20
Training Neural Networks Without Gradients: A ADMM Approach
Minineuralnets
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19
A framework for mini neural networks (perceptrons), written from scratch in python. The goal of the project is to demystify the workings of a neural network and various training algorithms by providing code written from scratch for the simplest neural network one could have.
Fdg
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16
Fully Decoupled Neural Network Learning Using Delayed Gradients (FDG)
Ascii Net
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16
A little experiment using neural networks to generate ASCII art
Neural Pgd
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16
This code implements the neural proximal gradient descent (PGD) algorithm proposed in https://arxiv.org/abs/1806.03963. The idea is to unroll the proximal gradient descent algorithm and model the proximal using a neural network. Adopting residual network (ResNet) as the proximal, a recurrent neural net (RNN) is implemented to learn the proximal. The code is flexible to incorporate various training costs such as pixel-wise l1/l2 cost, adversarial GAN, LSGAN, and WGAN.
Keras Padam
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16
Keras implementation of Padam from "Closing the Generalization Gap of Adaptive Gradient Methods in Training Deep Neural Networks"
Deeplearn
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15
OpenCL deep learning toolkit
Papers Of Nas
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15
Personal Digest of NAS (Under Construction 🛠)
Pg_rnn
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13
There are few caveats when you want to use a Recurrent Neural Network (RNN) policy with Policy Gradient Algorithms. This repository explains them and provide a solution for them. Please see the blog for more details.
Grokkingdeeplearning
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13
This repository will contain my take on Andrew Trask's book GrokkingDeepLearning.
Spytorch
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12
Tutorial for surrogate gradient learning in spiking neural networks
Cnnfromscratch
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12
Convolutional Neural Network in Matlab
Chainer Param Monitor
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12
Monitor parameter and gradient statistics during neural network training with Chainer
Robustbnns
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12
Code for paper "Robustness of Bayesian Neural Networks to Gradient-Based Attacks"
Neural Style Gradient
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11
Deeplearning_ai_books
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10
黄海广博士整理的【吴恩达】深度学习笔记
Fooling_neural_network Interpretations
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10
This repository provides a PyTorch implementation of "Fooling Neural Network Interpretations via Adversarial Model Manipulation". Our paper has been accepted to NeurIPS 2019.
Neuralnetwork
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9
Neural Network implementation in Numpy and Keras. Batch Normalization, Dropout, L2 Regularization and Optimizers
Machine Learning Assignments
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9
The assignment implementation of Coursera 「Machine Learning」
Library
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9
Paper reading list
Adversarial Attack On Recurrent Neural Network
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9
Implement adversarial arrack on Recurrent Neural network built to perform sentiment analysis with LSTM using TensorFlow
Binarynetconvolution
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9
Implement BinaryNet of CNN with chainer
Programming_assignments_of_deep_learning
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9
Keys for Programming Assignments of Coursera Course Deep Learning Specialization by Andrew Ng
Nnutils
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9
Neural networks in python
Dsci_572_sup Learn 2
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8
DSCI 572: Supervised Learning II
Nnlib
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8
🎓 Minimal neural networks library developed for educational purposes
Digit Recognizer
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8
A project I made to practice my newfound Neural Network knowledge - I used Python and Numpy to train a network to recognize MNIST images. Adam and mini-batch gradient descent implemented
Cnn_gradient_analysis
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8
Train a convolutional neural network and analyze the gradients in the model to identify relationships in high dimensional spaces.
Rnnpresentation
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7
RNNpresentation: A presentation about Recurrent Neural Network (RNN)
Pygrfnn
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7
Gradient Frequency Neural Networks, in Python
Machine_learning
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7
Machine Learning - Coursera.org
Adversarial.jl
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7
Adversarial attacks for Neural Networks written with FluxML
Mypythonneuralnetwork
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6
A neural network class in Python built from scratch
Synthetic Gradients Keras
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6
Keras implementation of `Decoupled Neural Interfaces using Synthetic Gradients`
Interp_regularization
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6
A novel neural network gradient regularization scheme for adversarial robustness and interpretability.
Geneticrnn
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6
A simple genetic training algorithm for recurrent neural networks
Neural Networks
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6
core neural network learning implementation based on back propagation algorithm
Tensorflow2.0_notebooks
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6
Implementation of a series of Neural Network architectures in TensorFow 2.0
Hamiltonian
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6
Speed up HMC with neural network gradient approximation
Carrot
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6
Carrot is a PyTorch neural network analysis tool using Dash.
Playwithdeeplearning
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6
Gradient Descent
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6
Let's learn gradient descent by using linear regression, logistic regression and neural networks!
Deep Learning Distilled
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5
Notes on some important deep learning topics and paper summaries
Deeplearning_cheatsheet_kor
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5
한눈에 살펴보는 딥러닝 관련 용어들
Crypto Forecasting With Neuralnetworks
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5
Feedforward and LSTM neural networks forecast our favourite financial markets. 🌊
Fully Connected Nn
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5
Fully Connected Neural Network
Froog
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5
neural network
Deep Learning Specialization Notes
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5
Things about the DL specialization from Coursera.
Explore Gradients
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5
Explore the problem of vanishing and exploding gradients
Ann Toolbox
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5
ANN Toolbox for Excel
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