# MV-LSTM
Multi-variable LSTM current neural networks for prediction and interpretation of multi-variable time series
Guo, Tian, Tao Lin, and Nino Antulov-Fantulin. "Exploring interpretable LSTM neural networks over multi-variable data." International Conference on Machine Learning (ICML). 2019.
Guo T, Lin T, Lu Y. An interpretable LSTM neural network for autoregressive exogenous model[J]. workshop track on ICLR, 2018.
The PyTorch implementation can be found here (credits go to KurochkinAlexey) :
https://github.com/KurochkinAlexey/IMV_LSTM
MV-LSTM:用于预测和解释多变量时间序列的多变量LSTM递归神经网络
需积分: 48 123 浏览量
2021-05-24
09:08:01
上传
评论 2
收藏 53KB ZIP 举报
MV-LSTM-master.zip （23个子文件） 
MV-LSTM-master 
config_hyper_para.py 5KB simplified_version utils_data_prep.py 18KB mv_rnn_cell.py 18KB ts_mv_rnn_attention.py 5KB ts_mv_rnn.py 30KB ts_mv_rnn_layers.py 6KB config_hyper_para_mv.py 1KB utils_libs.py 2KB main_mv_rnn.py 17KB ts_mv_rnn_eval.py 2KB config_data.json 2KB utils_causal.py 5KB utils_data_prep.py 15KB utils_results_analysis.py 3KB mv_rnn_cell.py 18KB train_mv_rnn.py 15KB ts_mv_rnn_attention.py 30KB ts_mv_rnn.py 46KB utils_libs.py 2KB README.md 553B ts_mv_rnn_basics.py 13KB config_data.json 7KB utils_causal.py 5KB资源评论
