Official implementation of the Seq-U-Net for efficient sequence modelling

(Realtime) Temporal Convolutions in PyTorch

TCNs

This research aims to predict video virality using a multimodal ensemble model. We're leveraging ConvLSTM Autoencoder for video encoding, NLP for audio analysis, and a transformer-based regression …

根据Seanny123复现论文A Dual-Stage Attention-Based Recurrent Neural Network for Time Series Prediction的pytorch代码进行相关修改，适应pytorch1.2版本

A Tensorflow 2 (Keras) implementation of DA-RNN (A Dual-Stage Attention-Based Recurrent Neural Network for Time Series Prediction, arXiv:1704.02971)

TCN-based sequence-to-sequence model for time series forecasting.

Qlib is an AI-oriented quantitative investment platform that aims to realize the potential, empower research, and create value using AI technologies in quantitative investment, from exploring ideas…

Keras version of LSTNet

Sequence to Sequence Learning with Keras

Rainfall Prediction or Rainfall Forecasting via machine learning, such as SVR, LSTM, MLP, Seq2Seq, GBRT and XGBoost

This project includes following repositories Presentation Machine Learning algorithms like Prophet, ARIMA, XGBoost, LSTM and Seq2Seq

lstm-rnn, seq2seq model and attention-seq2seq model for vessel trajectory prediction.

Implementation of Convolutional LSTM in PyTorch.

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

Time series forecasting especially in LSTF compare，include Informer, Autoformer, Reformer, Pyraformer, FEDformer, Transformer, MTGNN, LSTNet, Graph WaveNet

记录python,pytorch,git等工具的学习过程，主要是对该工具常用部分进行实践。

Python version of the Multivariate Empirical Mode Decomposition algorithm

LSTM + Wavelet（长短期记忆神经网络+小波分析）：深度学习与数字信号处理的结合

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

CEEMDAN-VMD-LSTM Forecasting model (a light version of CEEMDAN_LSTM)

Research about Particle Swarm Optimization (PSO) and it's implementation to optimize Artificial Neural Network (ANN)

Using Particle Swarm Optimization (PSO) to Optimize a CNN (Convulsional Neural Network) - using an simple dataset (not using an image dataset)

use PSO to train the sigle layer NN structure

粒子群算法优化支持向量机

PSO algorithm for multi-parameters optimizaiton

机器学习相关练手项目