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europython2016_dl-nlp

Introduction to Deep Learning for Natural Language Processing

ext-rescal

Scalable tensor factorization

eyescream

natural image generation using ConvNets

factorix

fairseq-py

Facebook AI Research Sequence-to-Sequence Toolkit written in Python.

faiss

A library for efficient similarity search and clustering of dense vectors.

fast-detection-of-overlapping-communities-via-online-tensor-methods

fast-rcnn

Fast R-CNN

faster-rcnn_tf

Faster-RCNN in Tensorflow

faster_rcnn

Faster R-CNN

fastfm

fastmaskrcnn

Mask RCNN in TensorFlow

fasttext

Library for fast text representation and classification.

fcnt

fftlda

Wang, Yining, et al. "Fast and Guaranteed Tensor Decomposition via Sketching." arXiv preprint arXiv:1506.04448 (2015). Downloaded from http://www.yining-wang.com/

firstcontactwithtensorflow

This repository contains the information required by the TensorFlow Hands-on at Summer Seminar ETSETB TelecomBCN, 4-8 July 2016

five-video-classification-methods

Code that accompanies my blog post outlining five video classification methods in Keras and TensorFlow

flann

Fast Library for Approximate Nearest Neighbors

flexifact

Run large scale tensor and coupled matrix-tensor factorization on top of stock Hadoop.

focal-loss

Focal loss for Dense Object Detection

fold

Deep learning with dynamic computation graphs in TensorFlow

gan_tutorial

ganhacks

starter from "How to Train a GAN?" at NIPS2016

gcn

Implementation of Graph Convolutional Networks in TensorFlow

genadv_tutorial

TensorFlow tutorial on Generative Adversarial Models

generative-adversarial-network-demo

Generative Adversarial Network Demo for Fresh Machine Learning #2

generative-adversarial-networks

Tutorial on GANs

generative-adversial

image generation via GANs

generative-models

Collection of generative models, e.g. GAN, VAE in Tensorflow, Keras, and Pytorch.

generativevideototextalignment

A hierarchical generative model for aligning video segments with corresponding text descriptions without manual supervision.