zhaoyibo61 Goto Github PK
Name: ZhaoYibo
Type: User
Name: ZhaoYibo
Type: User
Code for paper " AdderNet: Do We Really Need Multiplications in Deep Learning?"
A CNN and LSTM approach to predicting air quality
基于Keras的LSTM多变量时间序列预测
这是收集了很多的优秀的机器学习项目,将其做了整理
This repo includes introduction, code and dataset of our paper Deep Sequence Learning with Auxiliary Information for Traffic Prediction (KDD 2018).
Matlab code of Bayesian CP Factorization for Tensor Completion
Code for paper: Block Hankel Tensor ARIMA for Multiple Short Time Series Forecasting (AAAI-20)
Anomaly detection based on DNS traffic analysis
Block Term Decomposition for Caffe model
Caffe implementation of tucker tensor decomposition for convolutional layers
CCF CSP和PAT考试题解(使用C++11语法)
Analysis module for CleanAir Project, CNN & MLP to predict UFP (UltraFine Particles concentration) based on geospatial pollution measurements in a city
Bayesian Optimization-Based Global Optimal Rank Selection for Compression of Convolutional Neural Networks, IEEE Access
some ways to optimize CNN model
Reduce the computational complexity of a CNN by applying Tucker decomposition on pre-trained weights
利用情感语义分析和张量数据结构预测股价
Compression of NMT transformer model with tensor methods
In deep learning, a convolutional neural network (CNN, or ConvNet) is a class of deep, feed-forward artificial neural networks, most commonly applied to analyzing visual imagery. An autoencoder is a type of artificial neural network used to learn efficient data codings in an unsupervised manner. The aim of an autoencoder is to learn a representation (encoding) for a set of data, typically for dimensionality reduction.
CP Tensor Completion for Spatial Temporal Data
The CNN weight from "CP-decomposition with Tensor Power Method for Convolutional Neural Networks compression" (http://ieeexplore.ieee.org/document/7881725/)
Continuation of CP-TPM-CNN.. Based on my master thesis https://www.researchgate.net/publication/319623885_Deep_Compression_of_Convolutional_Neural_Networks_with_Low-Rank_Approximation
CP and Tucker decomposition for Convolutional Neural Networks
List of papers, code and experiments using deep learning for time series forecasting
机器学习和量化分析学习进行中
Successfully training approximations to full-rank matrices for efficiency in deep learning.
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.