TensorFlow implementations of a Restricted Boltzmann Machine and an unsupervised Deep Belief Network, including unsupervised fine-tuning of the Deep Belief Network.
-
Updated
Apr 1, 2017 - Python
TensorFlow implementations of a Restricted Boltzmann Machine and an unsupervised Deep Belief Network, including unsupervised fine-tuning of the Deep Belief Network.
Python implementation of "Sparse Local Embeddings for Extreme Multi-label Classification, NIPS, 2015"
PyTorch implementation of DEEP SUPERVISED HASHING FOR FAST IMAGE RETRIEVAL(CVPR 2016)
An Actor Critic Algorithm for Optimal Mortgage Refinancing
Object detection in video frames http://www.robots.ox.ac.uk/~vgg/publications/papers/sivic03.pdf
Recurrent Convolutional Neural Networks in PyTorch
A keras implementation of [Neural Arithmetic Logic Units](https://arxiv.org/pdf/1808.00508.pdf) by Andrew et. al.
A simple code of CycleGAN which is easy to read is implemented by TensorFlow
Tensorflow implementation of Importance Weighted Auto Encoder
Implementation for the KCM-F-GH of the paper "Gaussian kernel c-means hard clustering algorithms with automated computation of the width hyper-parameters"
Personal implementation of the paper "A two-stage ensemble method for the detection of class-label noise"
This is an implementation of the paper "Show and Tell: A Neural Image Caption Generator".
pytorch implementation of Independently Recurrent Neural Networks https://arxiv.org/abs/1803.04831
A complete Tensorflow implementation of cutout random erasing (without numpy)
This is a demo of the implementation of the program described in my Seminararbeit, a German paper typically written in 11th grade.
📝 ML Paper implementation of machine learning paper, ADASYN
Implementation of interesting papers
Perceptual_Losses_for_Real_Time_Style_Transfer
Add a description, image, and links to the paper-implementations topic page so that developers can more easily learn about it.
To associate your repository with the paper-implementations topic, visit your repo's landing page and select "manage topics."