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287 search results found

Neural Networks ⭐ 82

practical introduction to Python for neural networks, with keras and tensorflow - Oct 2016

Dl Uncertainty ⭐ 80

"What Uncertainties Do We Need in Bayesian Deep Learning for Computer Vision?", NIPS 2017 (unofficial code).

Deep Learning Tensorflow Book Code ⭐ 78

[『텐서플로로 배우는 딥러닝』, 솔라리스, 영진닷컴, 2018] 도서의 소스코드입니다.

Jestimator ⭐ 77

Amos optimizer with JEstimator lib.

Residual_block_keras ⭐ 74

Residual network block in Keras

Boltzmann ⭐ 68

Boltzmann energy-based deep learning techniques.

Label Embedding Network ⭐ 68

Label Embedding Network

AutoDiff DAG constructor, built on numpy and Cython. A Neural Turing Machine and DeepQ agent run on it. Clean code for educational purpose.

Dti Clustering ⭐ 65

(NeurIPS 2020 oral) Code for "Deep Transformation-Invariant Clustering" paper

Train the SGD model to recognize MNIST handwritten digits on local device

Mnist Challenge ⭐ 64

My solution to TUM's Machine Learning MNIST challenge 2016-2017 [winner]

Entropy Sgd ⭐ 61

Lua implementation of Entropy-SGD

Visualizingndf ⭐ 61

Official PyTorch implementation of "Visualizing the Decision-making Process in Deep Neural Decision Forest", CVPR 2019 Workshops on Explainable AI

Deep Learning in JS. Alternative to TensorFlow and ConvNetJS, that is 4x faster.

Gans 2.0 ⭐ 60

Generative Adversarial Networks in TensorFlow 2.0

Vae Gumbel Softmax ⭐ 60

An implementation of a Variational-Autoencoder using the Gumbel-Softmax reparametrization trick in TensorFlow (tested on r1.5 CPU and GPU) in ICLR 2017.

Assignment2 2017 ⭐ 59

(Spring 2017) Assignment 2: GPU Executor

How_to_generate_images ⭐ 59

This is the code for "How to Generate Images - Intro to Deep Learning #14' by Siraj Raval on YouTube

Excitationbp ⭐ 59

Visualizing how deep networks make decisions

Mnist Bnns ⭐ 59

Take MNIST TensorFlow deep neural network, run on iOS BNNS

Official implementation of the paper Stochastic Latent Residual Video Prediction

This repository is created to teach students about Machine Learning and Deep Learning using TensorFlow.

Caffe2 C Demo ⭐ 58

Show how to use Caffe2 in C++ through a simple LeNet sample project

Dl_study_with_gluon ⭐ 58

Deep Learning Study with Gluon

Deep Learning Multipliers ⭐ 57

Training deep neural networks with low precision multiplications

Bayesbyhypernet ⭐ 55

Code for the paper Implicit Weight Uncertainty in Neural Networks

Temporal Ensembling ⭐ 54

PyTorch implementation of Temporal Ensembling for Semi-Supervised Learning

Nvidia Docker Keras ⭐ 54

Workflow that shows how to train neural networks on EC2 instances with GPU support and compares training times to CPUs

Pytorch Pcgrad ⭐ 53

Pytorch reimplementation for "Gradient Surgery for Multi-Task Learning"

Pytorch_highway_networks ⭐ 53

Highway networks implemented in PyTorch.

Machinelearning ⭐ 52

โค้ดประกอบเนื้อหา Python Machine Learning เบื้องต้น

Deep Nlp ⭐ 52

Tensorflow Tutorial files and Implementations of various Deep NLP and CV Models.

Layerwise Relevance Propagation ⭐ 51

Implementation of Layerwise Relevance Propagation for heatmapping "deep" layers

Mnist Deep Learning ⭐ 50

Deep Learning codes for MNIST with detailed explanation

Hamaa: a Simple and Naive Deep Learning library.

Deep Unsupervised Image Hashing ⭐ 48

Implementation of accepted AAAI 2021 paper: Deep Unsupervised Image Hashing by Maximizing Bit Entropy

Denser Models ⭐ 47

This is outdated -- New version: https://github.com/boyangumn/DCN-New

Keras_odenet ⭐ 47

Implementation of (2018) Neural Ordinary Differential Equations on Keras

Ml In Tf ⭐ 45

Get started with Machine Learning in TensorFlow with a selection of good reads and implemented examples!

Deep Residual Networks Pyfunt ⭐ 45

Python implementation of "Deep Residual Learning for Image Recognition" (http://arxiv.org/abs/1512.03385 - MSRA, winner team of the 2015 ILSVRC and COCO challenges).

Implementation of some basic GAN architectures in Keras

Numpy Neuralnet Exercise ⭐ 42

Implementation of key concepts of neuralnetwork via numpy

Minerva Training Materials ⭐ 41

Learn advanced data science on real-life, curated problems

Tensorflow Crash Course ⭐ 41

For those who already have some basic idea about deep learning, and preferably are familiar with PyTorch.

Ruby Dnn ⭐ 40

ruby-dnn is a ruby deep learning library.

Strokenet ⭐ 40

a neural network that draws digits using strokes

An Open Convolutional Neural Network Framework in C++ From Scratch

Variational Dl ⭐ 40

Variational Deep Learning implementations, starting from simple Autoencoders.

Deepcompression ⭐ 39

implementation of Iterative Pruning for Deep neural network [Han2015].

Mnist For Numpy ⭐ 39

A simple, easy to use MNIST loader written in Python 3

A Lightweight & Flexible Deep Learning (Neural Network) Framework in Python

Conditional_vae ⭐ 37

conditional variational autoencoder written in Keras [not actively maintained]

Sukiyaki2 ⭐ 36

Deep Learning Library for JavaScript

Matlab Mnist Two Layer Perceptron ⭐ 36

A two layer perceptron implemented in MatLab to recognize handwritten digits based on the MNIST dataset.

Digiencoder ⭐ 36

A digit autoencoder for humans 🧬

Relativistic Average Gan Keras ⭐ 36

The implementation of Relativistic average GAN with Keras

Deep Learning Studio ⭐ 36

Contractive_autoencoder_in_pytorch ⭐ 34

Pytorch implementation of contractive autoencoder on MNIST dataset

Parametric Leaky Integrate And Fire Spiking Neuron ⭐ 34

Incorporating Learnable Membrane Time Constant to Enhance Learning of Spiking Neural Networks

Information Dropout ⭐ 34

Implementation of Information Dropout

Deep Embedded Clustering with Data Augmentation (DEC-DA). Performance on MNIST (acc=0.985, nmi=0.960).

Adasoptimizer ⭐ 33

ADAS is short for Adaptive Step Size, it's an optimizer that unlike other optimizers that just normalize the derivative, it fine-tunes the step size, truly making step size scheduling obsolete, achieving state-of-the-art training performance

Metric_learning ⭐ 33

Metric Learning App Dev Resource

Neural network library written in C and Javascript

Numpy Nn Model ⭐ 32

Сustom torch style machine learning framework with automatic differentiation implemented on numpy, allows build GANs, VAEs, etc.

Mnist Cudnn ⭐ 32

CUDA for MNIST training/inference

Implementation of Ladder Network in PyTorch.

Mnist_test ⭐ 29

mnist with Tensorflow

Cdcgan Keras ⭐ 29

Conditional Deep Convolutional GAN

Dataset Repair ⭐ 29

REPresentAtion bIas Removal (REPAIR) of datasets

Neural Network From Scratch ⭐ 29

Implementation of a neural network from scratch in python.

Randwire_tensorflow ⭐ 29

tensorflow implementation of Exploring Randomly Wired Neural Networks for Image Recognition

Compressed Transformer ⭐ 29

Compression of NMT transformer model with tensor methods

Handwritten Digit Recognition Tensorflowjs ⭐ 28

In-Browser Digit recognition with Tensorflow.js and React using Mnist dataset

Continual_learning_data_former ⭐ 28

A pytorch compatible data loader to create sequence of tasks for Continual Learning

Adda_mnist64 ⭐ 28

Adversarial Discriminative Domain Adaptation with MNIST 64x64 in Lasagne-Theano

Pytorch mnist example

Digit_recognizer ⭐ 27

CNN digit recognizer implemented in Keras Notebook, Kaggle/MNIST (0.995).

Handwritten digit recognizer using a feed-forward neural network and the MNIST dataset of 70,000 human-labeled handwritten digits.

Deepdefense.pytorch ⭐ 26

Implementation of our NeurIPS 2018 paper: Deep Defense: Training DNNs with Improved Adversarial Robustness

Mnist Multitask ⭐ 26

6️⃣6️⃣6️⃣ Reproduce ICLR '18 under-reviewed paper "MULTI-TASK LEARNING ON MNIST IMAGE DATASETS"

Deep Learning With Gdp Tensorflow ⭐ 26

Code to accompany the paper "Deep Learning with Gaussian Differential Privacy"

Pytorch implementation of TSSL-BP rule for Deep Spiking Neural Networks.

Deep K Means ⭐ 26

a deep recurrent model for exchangeable data

Softkmeans ⭐ 26

Implementation of Deep Soft-K means

Auxiliary Deep Generative Models ⭐ 25

Implementation of auxiliary deep generative models for semi-supervised learning

Mnist Neural Network Deeplearnjs ⭐ 25

🍃 Using a Neural Network to recognize MNIST digets in JavaScript.

Deeplearning ⭐ 25

Python implementation of UFLDL tutorial code

Deep Learning In R Using Keras And Tensorflow ⭐ 24

Implementing Deep learning in R using Keras and Tensorflow packages for R and implementing a Multi layer perceptron Model on MNIST dataset and doing Digit Recognition

A deep learning library to enable rapid prototyping

Tensorbag ⭐ 24

Collection of tensorflow notebooks tutorials for implementing the most important Deep Learning algorithms.

Pytorch implementation of paper Semi-supervised Knowledge Transfer for Deep Learning from Private Training Data (https://arxiv.org/abs/1610.05755)

Mnist Demo ⭐ 23

An interactive demonstration of single digit classification using deep artificial neural networks

Bayesian Compression For Deep Learning ⭐ 23

Remplementation of paper https://arxiv.org/abs/1705.08665

Tensorflow_basics ⭐ 23

Basic TensorFlow mechanics, operations, class definitions, and neural networks building. Examples from deeplearning.ai Tensorflow course using Google Colab platform.

A realtime digit OCR on the browser using Machine Learning

Quick Start ⭐ 22

FloydHub quick start project - train TensorFlow model with MNIST dataset

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