1182 Open source projects that are alternatives of or similar to probabilistic_nlg

Trimmed down {{mustache}} templates in .NET

Tensorflow implementation of adversarial auto-encoder for MNIST

Code for "MojiTalk: Generating Emotional Responses at Scale" https://arxiv.org/abs/1711.04090

텐서플로우를 기초부터 응용까지 단계별로 연습할 수 있는 소스 코드를 제공합니다

Tensorflow implementation of variational auto-encoder for MNIST

A repository for the paper "Improved Adversarial Systems for 3D Object Generation and Reconstruction".

Tensorflow implementation of conditional variational auto-encoder for MNIST

Annotated, understandable, and visually interpretable PyTorch implementations of: VAE, BIRVAE, NSGAN, MMGAN, WGAN, WGANGP, LSGAN, DRAGAN, BEGAN, RaGAN, InfoGAN, fGAN, FisherGAN

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A text-based widget toolkit

Theano implementation of Sequence-to-Sequence Autoencoder

Handle class imbalance intelligently by using variational auto-encoders to generate synthetic observations of your minority class.

This is a configurable generator to create random data like Lorum Ipsum Text, Words, Text Patterns, First/Last Names, MAC-Addresses, IP-Addresses, Guids and DateTime.

A Collection of Variational Autoencoders (VAE) in PyTorch.

でぃーぷらーにんぐを無限にやってディープラーニングでDeepLearningするための実装CheatSheet

HUAWEI 3D Modeling Kit project contains a sample app. Guided by this demo, you will be able to implement full 3D Modeling Kit capabilities, including 3D object reconstruction and material generation.

GPT-2 Telegram Chat bot

Source code for the NAACL 2019 paper "SEQ^3: Differentiable Sequence-to-Sequence-to-Sequence Autoencoder for Unsupervised Abstractive Sentence Compression"

This is the official implementation for IVA '19 paper "Analyzing Input and Output Representations for Speech-Driven Gesture Generation".

Deep Learning sample programs using PyTorch in C++

Advanced Deep Learning with Keras, published by Packt

This repository contains a new adversarial training method for Generative Conversational Agents

GPT-2 Telegram Chat bot

Compilation of the state of the art of tools, articles, forums and links of interest to generate and detect any type of synthetic content using deep learning.

Text Variational Autoencoder inspired by the paper 'Generating Sentences from a Continuous Space' Bowman et al. https://arxiv.org/abs/1511.06349

VideoEditor SDK: A fully customizable video editor for your app.

Selecton provides popup with actions on text selection in all major browsers

Lightweight: Faster than light, Low on memory

திருக்குறள் by திருவள்ளுவர்.

Helper with GUI to generate color codes such as CSS color notations.

Non-Linear Game Dialogue Editor

PyTorch study

S2VT (seq2seq) video captioning with bahdanau & luong attention implementation in Tensorflow

文本生成，可用于作诗、写小说

dcgan combined with vae in pytorch!

PyTorch port of the paper "Language to Logical Form with Neural Attention"

High quality web component for modal dialogs. Part of the Vaadin platform.

Matlab Toolbox for the Numerical Solution of Stochastic Differential Equations

fairseq: Convolutional Sequence to Sequence Learning (Gehring et al. 2017) by Chainer

💬 A simple framework to help displaying dialogs on a WPF app

Golang text generator for generate SEO texts

No description or website provided.

A tensorflow implementation of neural sequence-to-sequence parser for converting natural language queries to logical form.

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Performance comparison of existing GAN based Text To Image algorithms. (GAN-CLS, StackGAN, TAC-GAN)

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Regular expression for matching HTML comments

A simple unopinionated framework to implement simple modal based behaviour in angular (v2+) projects.

Implementation of the paper - Automatic chemical design using a data-driven continuous representation of molecules

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⚗ The most advanced CLI template on earth! Featuring automatic releases, website generation and a custom CI-System out of the box.

Simulate stochastic timeseries that follow ARFIMA, ARMA, ARIMA, AR, etc. processes

The easiest way to style custom text snippets in flutter

code for "Determining Gains Acquired from Word Embedding Quantitatively Using Discrete Distribution Clustering" ACL 2017

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Invariant representation learning from imaging and spectral data

Persistent multiplayer map of pins and stories.