A paper list for Time series modelling, including prediciton and anomaly detection
License: Apache License 2.0
deeptimeseriesmodel's Introduction
PaperList with Code
Time Series Model
A recurrent latent variable model for sequential data,NIPS 2015 [PDF] [Code]
Sequential neural models with stochastic layers,NIPS 2016 [PDF] [Code]
Structured Inference Networks for Nonlinear State Space Models,AAAI 2017 [PDF] [Code]
Factorized Inference in Deep Markov Models for Incomplete Multimodal Time Series,AAAI 2020 [PDF] [Code]
Multi-period Time Series Modeling with Sparsity via Bayesian Variational Inference,2017 [PDF] [Code]
Unsupervised Scalable Representation Learning for Multivariate Time Series,NeurIPS 2019 [PDF] [Code]
Time series decomposition
RobustSTL: A Robust Seasonal-Trend Decomposition Algorithm for Long Time Series,AAAI 2019 [PDF] [Code]
RobustTrend: A Huber Loss with a Combined First and Second Order Difference
Regularization for Time Series Trend Filtering,IJCAI 2019 [PDF] [Code]
Prediction
A Multi-Horizon Quantile Recurrent Forecaster,NIPS 2017 [PDF] [Code]
DeepAR: Probabilistic Forecasting with Autoregressive Recurrent Networks,2017 [PDF] [Code]
Deep Factors for Forecasting,ICML 2019 [PDF] [Code]
A Dual-Stage Attention-Based Recurrent Neural Network for Time Series Prediction,IJCAI 2017 [PDF] [Code]
Multilevel Wavelet Decomposition Network for Interpretable Time Series Analysis,KDD 2018 [PDF] [Code]
Deep State Space Models for Time Series Forecasting,NeurIPS 2018 [PDF] [Code]
Explainable Deep Neural Networks for Multivariate Time Series Predictions,IJCAI 2019 [PDF] [Code]
Modeling Extreme Events in Time Series Prediction,KDD 2018 [PDF] [Code]
Learning Interpretable Deep State Space Model for Probabilistic Time Series Forecasting,IJCAI 2019 [PDF] [Code]
Shape and Time Distortion Loss for Training Deep Time Series Forecasting Models,NeurIPS 2019 [PDF] [Code]
Enhancing the Locality and Breaking the Memory Bottleneck of Transformer on Time Series Forecasting,NeurIPS 2019 [PDF] [Code]
Anomaly Detection
LSTM-based encoder-decoder for multi-sensor anomaly detection,2016 [PDF] [Code]
Anomaly Detection in Streams with Extreme Value Theory,KDD 2017 [PDF] [Code]
Robust Anomaly Detection for Multivariate Time Series through Stochastic Recurrent Neural Network,KDD 2019 [PDF] [Code]
Detecting Spacecraft Anomalies Using LSTMs and Nonparametric Dynamic Thresholding,KDD 2018 [PDF] [Code]
A Deep Neural Network for Unsupervised Anomaly Detection and Diagnosis in Multivariate Time Series Data,AAAI 2019 [PDF] [Code]
BeatGAN: Anomalous Rhythm Detection using Adversarially Generated Time Series,IJCAI 2019 [PDF] [Code]
Deep Anomaly Detection with Deviation Networks,KDD 2019 [PDF] [Code]
Deep autoencoding gaussian mixture model for unsupervised anomaly detection,ICLR 2018 [PDF] [Code]
A Multimodal Anomaly Detector for Robot-Assisted Feeding Using an LSTM-based Variational Autoencoder,IEEE Robotics and Automation Letters 2018 [PDF] [Code]
MAD-GAN: Multivariate Anomaly Detection for Time Series Data with Generative Adversarial Networks,2019 [PDF] [Code]
Outlier Detection for Time Series with Recurrent Autoencoder Ensembles,IJCAI 2019 [PDF] [Code]
Sequential Anomaly Detection using Inverse Reinforcement Learning,KDD 2019 [PDF] [Code]
Sparse Modeling-Based Sequential Ensemble Learning for Effective Outlier Detection in High-Dimensional Numeric Data,AAAI 2018 [PDF] [Code]
Time-Series Anomaly Detection Service at Microsoft,KDD 2019 [PDF] [Code]
Unsupervised Anomaly Detection for Intricate KPIs via Adversarial Training of VAE,INFOCOM 2019 [PDF] [Code]
Unsupervised Anomaly Detection via Variational Auto-Encoder for Seasonal KPIs in Web Applications,WWW 2018 [PDF] [Code]
Others
Modeling Combinatorial Evolution in Time Series Prediction,2019 [PDF] [Code]
SOM-VAE: Interpretable Discrete Representation Learning on Time Series,ICLR 2019 [PDF] [Code]
Variational PSOM: Deep Probabilistic Clustering with Self-Organizing Maps,2019 [PDF] [Code]
Time2Graph: Revisiting Time Series Modeling with Dynamic Shapelets,AAAI 2020 [PDF] [Code]
Multivariate Time Series Imputation with Variational Autoencoders,2019 [PDF] [Code]