Et6an

Et6an's Stars

• thuml/iTransformer

  Official implementation for "iTransformer: Inverted Transformers Are Effective for Time Series Forecasting" (ICLR 2024 Spotlight), https://openreview.net/forum?id=JePfAI8fah

  Language:Python1.1k199

• speedinghzl/CCNet

  CCNet: Criss-Cross Attention for Semantic Segmentation (TPAMI 2020 & ICCV 2019).

  Language:Python1.4k276

• dair-ai/ml-visuals

  🎨 ML Visuals contains figures and templates which you can reuse and customize to improve your scientific writing.

  13.1k1.4k

• timeseriesAI/tsai

  Time series Timeseries Deep Learning Machine Learning Python Pytorch fastai | State-of-the-art Deep Learning library for Time Series and Sequences in Pytorch / fastai

  Language:Jupyter Notebook5.1k639

• DataForScience/Timeseries

  Timeseries for everyone

  Language:Jupyter Notebook245115

• lizongying/my-tv

  我的电视 电视直播软件，安装即可使用

  Language:C29.6k3.3k

• xmu-xiaoma666/External-Attention-pytorch

  🍀 Pytorch implementation of various Attention Mechanisms, MLP, Re-parameter, Convolution, which is helpful to further understand papers.⭐⭐⭐

  Language:Python11.3k1.9k

• ariaghora/robust-period

  Unofficial Implementation of RobustPeriod: Time-Frequency Mining for Robust Multiple Periodicities Detection

  Language:Python9114

• choyi0521/WaveBound

  Language:Python211

• thuml/Autoformer

  About Code release for "Autoformer: Decomposition Transformers with Auto-Correlation for Long-Term Series Forecasting" (NeurIPS 2021), https://arxiv.org/abs/2106.13008

  Language:Jupyter Notebook1.9k410

• Time9Y/Matlab-Machine

  Language:MATLAB690141

• WhisperRen/TPA-LSTM_in_tf2

  Implementation of TPA-LSTM in TensorFlow2

  Language:Python172

• lixus7/Time-Series-Works-Conferences

  Time-Series Work Summary in CS Top Conferences (NIPS, ICML, ICLR, KDD, AAAI, WWW, IJCAI, CIKM, ICDM, ICDE, etc.)

  77583

• philipperemy/keras-tcn

  Keras Temporal Convolutional Network.

  Language:Python1.9k454

• abhishekdabas31/Stock-Prediction-

  Time Series analysis using Oscillation Box and prediction using ELM model

  Language:Jupyter Notebook1

• fish-kong/CSDN-code-link

  由于CSDN博客里面不能直接上代码链接，涉嫌营销推广，因此建一个github仓库用于整理这些代码链接

  15221

• currylym/time-series-prediction-learning-record

  Learning Record about TSP

  5810

• laiguokun/LSTNet

  Language:Python650169

• wqk666999/CNN-LSTM-Attention

  使用卷积神经网络-长短期记忆网络（bi-LSTM）-注意力机制对股票收盘价进行回归预测。The convolution neural network, short-term memory network and attention mechanism are used to predict the closing price.

  21642

• nicodjimenez/lstm

  Minimal, clean example of lstm neural network training in python, for learning purposes.

  Language:Python1.7k651

• facebookresearch/segment-anything

  The repository provides code for running inference with the SegmentAnything Model (SAM), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.

  Language:Jupyter Notebook46.7k5.5k

• thuml/Time-Series-Library

  A Library for Advanced Deep Time Series Models.

  Language:Python6.3k1k

• sksujan58/Multivariate-time-series-forecasting-using-LSTM

  Language:Jupyter Notebook22992

• elbuco1/CBAM

  CBAM: Convolutional Block Attention Module for CIFAR10 on ResNet backbone with Pytorch

  Language:Python10130

• tangxianfeng/STDN

  Code for our Spatiotemporal Dynamic Network

  Language:Python27598

• DHI/tsod

  Anomaly Detection for time series data

  Language:Python15918

• stxupengyu/Multi-LSTM-for-Regression

  使用LSTM处理回归问题，每个输入特征的时间窗维度不一样，因此，也可以看作利用了多个LSTM特征提取器。When LSTM is used to deal with regression problems, the time window dimension of each input feature is different. Therefore, it can also be regarded as using multiple LSTM feature extractors.

  Language:Jupyter Notebook81

• zhouhaoyi/ETDataset

  The Electricity Transformer dataset is collected to support the further investigation on the long sequence forecasting problem.

  640126

• zhouhaoyi/Informer2020

  The GitHub repository for the paper "Informer" accepted by AAAI 2021.

  Language:Python5.3k1.1k

• FateMurphy/CEEMDAN_LSTM

  CEEMDAN_LSTM is a Python project for decomposition-integration forecasting models based on EMD methods and LSTM.

  Language:Jupyter Notebook21642