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Name: Yunzhe Hao
Type: User
Company: CASIA
Bio: PhD student @ CASIA; Main interests include Speech Separation, Auditory Attention, Spiking Neural Network
Location: Beijing China
Name: Yunzhe Hao
Type: User
Company: CASIA
Bio: PhD student @ CASIA; Main interests include Speech Separation, Auditory Attention, Spiking Neural Network
Location: Beijing China
AcadHomepage: A Modern and Responsive Academic Personal Homepage
Google AI 2018 BERT pytorch implementation
Spatio-temporal BP for SNNs
Implementation of Convolutional LSTM in PyTorch.
Real Time Speech Enhancement in the Waveform Domain (Interspeech 2020)We provide a PyTorch implementation of the paper Real Time Speech Enhancement in the Waveform Domain. In which, we present a causal speech enhancement model working on the raw waveform that runs in real-time on a laptop CPU. The proposed model is based on an encoder-decoder architecture with skip-connections. It is optimized on both time and frequency domains, using multiple loss functions. Empirical evidence shows that it is capable of removing various kinds of background noise including stationary and non-stationary noises, as well as room reverb. Additionally, we suggest a set of data augmentation techniques applied directly on the raw waveform which further improve model performance and its generalization abilities.
A PyTorch implementation of dual-path RNNs (DPRNNs) based speech separation described in "Dual-path RNN: efficient long sequence modeling for time-domain single-channel speech separation".
End-to-End Speech Processing Toolkit
C++ extensions in PyTorch
A faster pytorch implementation of faster r-cnn
FasterRCNN is implemented in VGG, ResNet and FPN base.
A PyTorch implementation of the FFTNet: a Real-Time Speaker-Dependent Neural Vocoder
Google Research
A PyTorch implementation of Listen, Attend and Spell (LAS), an End-to-End ASR framework.
Executable code based on Google articles
Plain python implementations of basic machine learning algorithms
My blogs and code for machine learning. http://cnblogs.com/pinard
Neural end-to-end Speech Translation Toolkit
An unofficial and partial Keras implementation of "Noise2Noise: Learning Image Restoration without Clean Data"
An implementation of Performer, a linear attention-based transformer, in Pytorch
PyTorch implementation of Contrastive Learning methods; List of awesome-contrastive-learning papers
Practice on cifar100(ResNet, DenseNet, VGG, GoogleNet, InceptionV3, InceptionV4, Inception-ResNetv2, Xception, Resnet In Resnet, ResNext,ShuffleNet, ShuffleNetv2, MobileNet, MobileNetv2, SqueezeNet, NasNet, Residual Attention Network, SENet)
DeepLab resnet v2 model in pytorch
pytorch1.0 updated. Support cpu test and demo.
PyTorch implementation of the Quasi-Recurrent Neural Network - up to 16 times faster than NVIDIA's cuDNN LSTM
MobileNetV1, MobileNetV2, VGG based SSD/SSD-lite implementation in Pytorch 1.0 / Pytorch 0.4. Out-of-box support for retraining on Open Images dataset. ONNX and Caffe2 support. Experiment Ideas like CoordConv.
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.