afcarl Goto Github PK

discussionsummarization

Discussion Summarization is the process of condensing a text document which is a collection of discussion threads, using CBS (Cluster Based Summarization) approach in order to create a relevant summary which enlists most of the important points of the original thematic discussion, thereby providing the users, both concise and comprehensive piece of information. This outlines all the opinions which are described from multiple perspectives in a single document. This summary is completely unbiased as they present information extracted from multiple sources based on a designed algorithm, without any editorial touch or subjective human intervention. Extractive methods used here, follow the technique of selecting a subset of existing words, phrases, or sentences in the original text to form the summary. An iterative ranking algorithm is followed for clustering. The NLP (Natural Language Processing) is used to process human language data. Precisely, it is applied while working with corpora, categorizing text, analyzing linguistic structure. Thus, the quick summary is aimed at being salient, relevant and non-redundant. The proposed model is validated by testing its ability to generate optimal summary of discussions in Yahoo Answers. Results show that the proposed model is able to generate much relevant summary when compared to present summarization techniques.

disentangled-person-image-generation

Tensorflow implementation of CVPR 2018 paper "Disentangled Person Image Generation"

disimrank

Gene target ranking by driven input single input motif Matlab code.

diskbenchmark

Benchmarking utilities for measuring the latencies of disks (mostly interesting for SSDs).

disklavier-parser

For converting MIDI files in the Yamaha Disklavier enhanced MIDI format into text files and back

dist-a3c

Distributed A3C

dist-based-model4bwe

PyTorch implementation of "A Distribution-based Model to Learn Bilingual Word Embeddings" (Cao et al., COLING2016)

dist-keras

Distributed Deep Learning, with a focus on distributed training, using Keras and Apache Spark.

distarray

Distributed NumPy-like arrays, ufuncs, and more. Think globally, act locally.

distnndl

Distributed training of neural networks using NNDL

distortions

Image distortion tool.

distributed

Distributed computation in Python

distributed-tensorflow-example

An example of data parallelism and async updates of parameter in tensorflow.

distributed-tensorflow-guide

Distributed TensorFlow basics and examples of training algorithms

distributed_denial_of_service_ddos

distributed_memory_mpi

Distributed memory with MPI in Python, features also map/reduce/filter!

distributed_rl

Pytorch implementation of distributed deep reinforcement learning

distributed_skipgram_mixture

Distributed skipgram mixture model for multisense word embedding

distributed_tensorflow_gentle_introduction

Jupyter notebook running through some basic examples of Distributed TensorFlow

distributed_word_embedding

Distributed word embedding

distributeddeeplearningreads

Papers and blogs related to distributed deep learning

distributedes

Distributed implementation of popular evolutionary methods

distribution-cheatsheet

A lookup repo for a variety of distributions (implemented in Python)

distributional_rl

Repository for studying distributional rl

distributionawarebinarizednetworks-wacv18

Distribution-Aware Binarization of Neural Networks for Sketch Recognition - WACV 18

distributions

Low-level primitives for collapsed Gibbs sampling in python and C++

distro

Torch installation in a self-contained folder

distrom

Distributed Multinomial Regression

distsys-class

Class materials for a distributed systems lecture series

ditchdaddy

Ditch GoDaddy, join the DNSimple/Namecheap/Gandi.net party