zhuannianyixiang

zhuannianyixiang's Stars

• thuml/MADA

  Code release for "Multi-Adversarial Domain Adaptation" (AAAI 2018)

  Language:C++5617

• Luodian/MADAN

  Pytorch Code release for our NeurIPS paper "Multi-source Domain Adaptation for Semantic Segmentation"

  Language:Python17127

• agrija9/Deep-Unsupervised-Domain-Adaptation

  Pytorch implementation of four neural network based domain adaptation techniques: DeepCORAL, DDC, CDAN and CDAN+E. Evaluated on benchmark dataset Office31.

  Language:Python8022

• thuml/CDAN

  Code release for "Conditional Adversarial Domain Adaptation" (NIPS 2018)

  Language:Jupyter Notebook39492

• thuml/Transfer-Learning-Library

  Transfer Learning Library for Domain Adaptation, Task Adaptation, and Domain Generalization

  Language:Python3.3k551

• jindongwang/transferlearning

  Transfer learning / domain adaptation / domain generalization / multi-task learning etc. Papers, codes, datasets, applications, tutorials.-迁移学习

  Language:Python13.3k3.8k

• analyticalmindsltd/smote_variants

  A collection of 85 minority oversampling techniques (SMOTE) for imbalanced learning with multi-class oversampling and model selection features

  Language:Jupyter Notebook625138

• duxiaoqin/VGAE

  Reimplementation of paper "Variational Graph Auto-Encoders", adapted from https://github.com/limaosen0/Variational-Graph-Auto-Encoders/, simplified and error-corrected.

  Language:Python123

• wiseodd/generative-models

  Collection of generative models, e.g. GAN, VAE in Pytorch and Tensorflow.

  Language:Python7.3k2k

• AntixK/PyTorch-VAE

  A Collection of Variational Autoencoders (VAE) in PyTorch.

  Language:Python6.5k1.1k

• dennybritz/chatbot-retrieval

  Dual LSTM Encoder for Dialog Response Generation

  Language:Jupyter Notebook1.6k674

• Grzego/handwriting-generation

  Implementation of handwriting generation with use of recurrent neural networks in tensorflow. Based on Alex Graves paper (https://arxiv.org/abs/1308.0850).

  Language:Python528107

• FernandoLpz/Text-Generation-BiLSTM-PyTorch

  In this repository you will find an end-to-end model for text generation by implementing a Bi-LSTM-LSTM based model with PyTorch's LSTMCells.

  Language:Python4720

• campdav/Text-Generation-using-Bidirectional-LSTM-and-Doc2Vec-models

  Text Generation using Bidirectional LSTM and Doc2Vec models

  Language:Jupyter Notebook6236

• felix-last/kmeans_smote

  Oversampling for imbalanced learning based on k-means and SMOTE

  Language:Python11858

• dd1github/DeepSMOTE

  Pytorch implementation of "DeepSMOTE: Fusing Deep Learning and SMOTE for Imbalanced Data".

  Language:Python10230

• WadeStack/BigDataIE

  大数据博客、笔试题、教程、项目、面经的整理

  550130

• enhaofrank/Data-mining-or-data-analysis

  数据分析或者数据挖掘工程师面试题整理

  13620

• taizilongxu/interview_python

  关于Python的面试题

  Language:Shell16.5k5.5k

• stxupengyu/ARIMA-Plot-of-Residuals

  使用AIC准则进行参数选择，之后采用ARIMA模型进行时间序列预测，最后给出残差图。The AIC criterion is used to select the parameters, and then ARIMA model is used to predict the time series. Finally, the residual diagram is given.

  Language:Jupyter Notebook61

• ningmengwei-ata/Capacity-Forecast-with-TTE

  Undergradute final project with ARIMA,LSTM,GRU,Xgboost and DeepTTE.毕业论文代码库合集，包括基于ARIMA,LSTM,GRU进行时间序列预测，基于DeepTTE解决ETA(estimated time of arrival)问题计算运输完成时长，基于特征工程和xgboost的运力预测

  Language:Jupyter Notebook17

• litaolemo/Research

  使用ARIMA,Transformer,LSTM 对心跳时间序列数据进行预测

  Language:Jupyter Notebook13

• Ultraopxt/ARIMA-time-series-analysis-forecasting-restaurant-sales

  ARIMA时间序列分析：预测餐厅销量

  Language:Jupyter Notebook61

• yangwohenmai/TimeSeriesForecasting

  基于统计学的时间序列预测(AR,ARM).

  Language:Python23475

• HuiDBK/LogSetupDemo

  Python中使用logging日志模块，来记录程序运行信息

  Language:Python85

• afatcoder/LeetcodeTop

  汇总各大互联网公司容易考察的高频leetcode题🔥

  18.6k2.7k

• fungtion/DANN_py3

  python 3 pytorch implementation of DANN

  Language:Python50696

• fungtion/DANN

  pytorch implementation of Domain-Adversarial Training of Neural Networks

  Language:Python831149

• tensorlayer/DCGAN

  The Simplest DCGAN Implementation

  Language:Python337115

• sarajcev/PSS-ML

  Machine learning for power system stability analysis

  Language:Jupyter Notebook142