WavegradImplementation of Google Brain's WaveGrad high-fidelity vocoder (paper: https://arxiv.org/pdf/2009.00713.pdf). First implementation on GitHub.
Stars: ✭ 245 (+131.13%)
AsrgenAttacking Speaker Recognition with Deep Generative Models
Stars: ✭ 31 (-70.75%)
ParallelwaveganUnofficial Parallel WaveGAN (+ MelGAN & Multi-band MelGAN) with Pytorch
Stars: ✭ 682 (+543.4%)
Generative ModelsAnnotated, understandable, and visually interpretable PyTorch implementations of: VAE, BIRVAE, NSGAN, MMGAN, WGAN, WGANGP, LSGAN, DRAGAN, BEGAN, RaGAN, InfoGAN, fGAN, FisherGAN
Stars: ✭ 438 (+313.21%)
Dsprites DatasetDataset to assess the disentanglement properties of unsupervised learning methods
Stars: ✭ 340 (+220.75%)
Tf VqvaeTensorflow Implementation of the paper [Neural Discrete Representation Learning](https://arxiv.org/abs/1711.00937) (VQ-VAE).
Stars: ✭ 226 (+113.21%)
Pytorch Dc TtsText to Speech with PyTorch (English and Mongolian)
Stars: ✭ 122 (+15.09%)
Neural OdeJupyter notebook with Pytorch implementation of Neural Ordinary Differential Equations
Stars: ✭ 335 (+216.04%)
NemoNeMo: a toolkit for conversational AI
Stars: ✭ 3,685 (+3376.42%)
Tts🤖 💬 Deep learning for Text to Speech (Discussion forum: https://discourse.mozilla.org/c/tts)
Stars: ✭ 5,427 (+5019.81%)
Joint VaePytorch implementation of JointVAE, a framework for disentangling continuous and discrete factors of variation 🌟
Stars: ✭ 404 (+281.13%)
Cs224n Gpu That TalksAttention, I'm Trying to Speak: End-to-end speech synthesis (CS224n '18)
Stars: ✭ 52 (-50.94%)
VAENAR-TTSPyTorch Implementation of VAENAR-TTS: Variational Auto-Encoder based Non-AutoRegressive Text-to-Speech Synthesis.
Stars: ✭ 66 (-37.74%)
Deep Learning With PythonExample projects I completed to understand Deep Learning techniques with Tensorflow. Please note that I do no longer maintain this repository.
Stars: ✭ 134 (+26.42%)
Vae TensorflowA Tensorflow implementation of a Variational Autoencoder for the deep learning course at the University of Southern California (USC).
Stars: ✭ 117 (+10.38%)
Pytorch VaeA CNN Variational Autoencoder (CNN-VAE) implemented in PyTorch
Stars: ✭ 181 (+70.75%)
Pytorch Vq VaePyTorch implementation of VQ-VAE by Aäron van den Oord et al.
Stars: ✭ 204 (+92.45%)
Parallel-Tacotron2PyTorch Implementation of Google's Parallel Tacotron 2: A Non-Autoregressive Neural TTS Model with Differentiable Duration Modeling
Stars: ✭ 149 (+40.57%)
Tts🐸💬 - a deep learning toolkit for Text-to-Speech, battle-tested in research and production
Stars: ✭ 305 (+187.74%)
Tacotron2pytorch tacotron2 https://arxiv.org/pdf/1712.05884.pdf
Stars: ✭ 46 (-56.6%)
Vae protein functionProtein function prediction using a variational autoencoder
Stars: ✭ 57 (-46.23%)
Kaggle Ds Bowl 2018 BaselineFull train/inference/submission pipeline adapted to the competition from https://github.com/matterport/Mask_RCNN
Stars: ✭ 105 (-0.94%)
Sharing isl pythonAn Introduction to Statistical Learning with Applications in PYTHON
Stars: ✭ 105 (-0.94%)
Anomaly DetectionAnomaly detection algorithm implementation in Python
Stars: ✭ 105 (-0.94%)
Face ClassificationFace model to classify gender and race. Trained on LFWA+ Dataset.
Stars: ✭ 104 (-1.89%)
DmmDeep Markov Models
Stars: ✭ 103 (-2.83%)
Ossdc VisionbasedaccDiscuss requirments and develop code for #1-mvp-vbacc MVP (see also this channel on ossdc.org Slack)
Stars: ✭ 104 (-1.89%)
YaboxYet another black-box optimization library for Python
Stars: ✭ 103 (-2.83%)
Practical Ml W PythonSource code for 'Practical Machine Learning with Python' by Dipanjan Sarkar, Raghav Bali, and Tushar Sharma
Stars: ✭ 104 (-1.89%)
Intro machine learningIntroduction to Machine Learning, a series of IPython Notebook and accompanying slideshow and video
Stars: ✭ 105 (-0.94%)
WavernnWaveRNN Vocoder + TTS
Stars: ✭ 1,636 (+1443.4%)
BoxdetectionA Box detection algorithm for any image containing boxes.
Stars: ✭ 104 (-1.89%)
Tacotron PytorchA Pytorch Implementation of Tacotron: End-to-end Text-to-speech Deep-Learning Model
Stars: ✭ 104 (-1.89%)
Gen QuickstartDocker file for building Gen and Jupyter notebooks for tutorials and case studies
Stars: ✭ 104 (-1.89%)
Pixel2style2pixelOfficial Implementation for "Encoding in Style: a StyleGAN Encoder for Image-to-Image Translation"
Stars: ✭ 1,395 (+1216.04%)
Unet Segmentation In Keras TensorflowUNet is a fully convolutional network(FCN) that does image segmentation. Its goal is to predict each pixel's class. It is built upon the FCN and modified in a way that it yields better segmentation in medical imaging.
Stars: ✭ 105 (-0.94%)
Ec2 Spot WorkshopsCollection of workshops to demonstrate best practices in using Amazon EC2 Spot Instances. https://aws.amazon.com/ec2/spot/
Stars: ✭ 104 (-1.89%)
ManipulationCourse notes for MIT manipulation class
Stars: ✭ 105 (-0.94%)
OpenomniDocumentation and library for decoding omnipod communications.
Stars: ✭ 105 (-0.94%)
How To Generate Art DemoThis is the code for "How to Generate Art - Intro to Deep Learning #8' by Siraj Raval on YouTube
Stars: ✭ 105 (-0.94%)
D2l Torch《动手学深度学习》 PyTorch 版本
Stars: ✭ 105 (-0.94%)
Nlp essentialsEssential and Fundametal aspects of Natural Language Processing with hands-on examples and case-studies
Stars: ✭ 104 (-1.89%)
Spokestack PythonSpokestack is a library that allows a user to easily incorporate a voice interface into any Python application.
Stars: ✭ 103 (-2.83%)
FmaFMA: A Dataset For Music Analysis
Stars: ✭ 1,391 (+1212.26%)