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TimeSeries.md

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Time series analysis

AAAI

2019

Classification

Deep Transformation Method for Discriminant Feature Extraction from Multi-Channel Time Series Data

Adversarial Unsupervised Representation Learning for Activity Time-Series

Anomaly Detection

A Deep Neural Network for Unsupervised Anomaly Detection and Diagnosis in Multivariate Time Series Data

Forecasting

Cogra: Concept-drift-aware Stochastic Gradient Descent for Time-series Forecasting

Imputation

Estimating the Causal Effect from Partially Observed Time Series

Decomposition

RobustSTL: A Robust Seasonal-Trend Decomposition Procedure for Long Time Series

Interdiscipline

Exploiting Time-Series Image-to-Image Translation to Expand the Range of Wildlife Habitat Analysis

2020

Classification

TapNet: Multivariate Time Series Classificationwith Attentional Prototype Network

Forecasting

DATA-GRU: Dual-Attention Time-Aware Gated Recurrent Unit for Irregular Multivariate Time Series

Joint Modeling of Local and Global Temporal Dynamics for Multivariate Time Series Forecasting with Missing Values

Tensorized LSTM with Adaptive Shared Memory for Learning Trends in Multivariate Time Series

Block Hankel Tensor ARIMA for Multiple Short Time Series Forecasting

Imputation

Factorized Inference in Deep Markov Models for Incomplete Multimodal Time Series

Representation learning

Deep Unsupervised Binary Coding Networks for Multivariate Time Series Retrieval

Relation Inference among Sensor Time Series in Smart Buildings with Metric Learning

Time2Graph: Revisiting Time Series Modeling with Dynamic Shapelets

2021

Classification

Correlative Channel-Aware Fusion for Multi-View Time Series Classification

Learnable Dynamic Temporal Pooling for Time Series Classification

ShapeNet: A Shapelet-Neural Network Approach for Multivariate Time Series Classification

Joint-Label Learning by Dual Augmentation for Time Series Classification

Clustering

Learning Representations for Incomplete Time Series Clustering

Forecasting

Deep Switching Auto-Regressive Factorization: Application to Time Series Forecasting

Dynamic Gaussian Mixture Based Deep Generative Model for Robust Forecasting on Sparse Multivariate Time Series

Temporal Latent Autoencoder: A Method for Probabilistic Multivariate Time Series Forecasting

Synergetic Learning of Heterogeneous Temporal Sequences for Multi-Horizon Probabilistic Forecasting

Anomaly Detection

Graph Neural Network-Based Anomaly Detection in Multivariate Time Series

Time Series Anomaly Detection with Multiresolution Ensemble Decoding

Outlier Impact Characterization for Time Series Data

Imputation

Generative Semi-Supervised Learning for Multivariate Time Series Imputation

Interdiscipline

Time Series Domain Adaptation via Sparse Associative Structure Alignment

2022

Anomaly Detection

AnomalyKiTS: Anomaly Detection Toolkit for Time Series

Clustering Interval-Censored Time-Series for Disease Phenotyping

Towards a Rigorous Evaluation of Time-Series Anomaly Detection

Analysis

Training Robust Deep Models for Time-Series Domain: Novel Algorithms and Theoretical Analysis

Representation Learning

I-SEA: Importance Sampling and Expected Alignment-Based Deep Distance Metric Learning for Time Series Analysis and Embedding

TS2Vec: Towards Universal Representation of Time Series

Forecasting

Reinforcement Learning Based Dynamic Model Combination for Time Series Forecasting

CATN: Cross Attentive Tree-Aware Network for Multivariate Time Series Forecasting

Mitigating Low Agricultural Productivity of Smallholder Farms in Africa: Time-Series Forecasting for Environmental Stressors

Generation

Conditional Loss and Deep Euler Scheme for Time Series Generation

IJCAI

2019

Clustering

Linear Time Complexity Time Series Clustering with Symbolic Pattern Forest

Similarity Preserving Representation Learning for Time Series Clustering

Forecasting

Learning Interpretable Deep State Space Model for Probabilistic Time Series Forecasting

RobustTrend: A Huber Loss with a Combined First and Second Order Difference Regularization for Time Series Trend Filtering

Explainable Deep Neural Networks for Multivariate Time Series Predictions

Anomaly Detection

BeatGAN: Anomalous Rhythm Detection using Adversarially Generated Time Series

Outlier Detection for Time Series with Recurrent Autoencoder Ensembles

Imputation

E^2GAN: End-to-End Generative Adversarial Network for Multivariate Time Series Imputation

2020

Classification

A new attention mechanism to classify multivariate time series

Forecasting

The Squawk Bot: Joint Learning of Time Series and Text Data Modalities for Automated Financial Information Filtering

A Quantum-inspired Entropic Kernel for Multiple Financial Time Series Analysis

WATTNet: Learning to Trade FX via Hierarchical Spatio-Temporal Representation of Highly Multivariate Time Series

2021

Classification

Time-Series Representation Learning via Temporal and Contextual Contrasting

Forecasting

TE-ESN: Time Encoding Echo State Network for Prediction Based on Irregularly Sampled Time Series Data

Time-Aware Multi-Scale RNNs for Time Series Modeling

Two Birds with One Stone: Series Saliency for Accurate and Interpretable Multivariate Time Series Forecasting

Multi-series Time-aware Sequence Partitioning for Disease Progression Modeling

Unsupervised Domain Adaptation

Adversarial Spectral Kernel Matching for Unsupervised Time Series Domain Adaptation

2022

Classification

T-SMOTE: Temporal-oriented Synthetic Minority Oversampling Technique for Imbalanced Time Series Classification A Reinforcement Learning-Informed Pattern Mining Framework for Multivariate Time Series Classification

Forecasting

Triformer: Triangular, Variable-Specific Attentions for Long Sequence Multivariate Time Series Forecasting Memory Augmented State Space Model for Time Series Forecasting DeepExtrema: A Deep Learning Approach for Forecasting Block Maxima in Time Series Data

Anomaly Detection

GRELEN: Multivariate Time Series Anomaly Detection from the Perspective of Graph Relational Learning Neural Contextual Anomaly Detection for Time Series

SIGMOD

2019

Root-cause analysis

ExplainIt! -- A declarative root-cause analysis engine for time series data

2020

Distance Measures

Debunking Four Long-Standing Misconceptions of Time-Series Distance Measures

Analysis

Database Workload Capacity Planning using Time Series Analysis and Machine Learning

2021

Periodicity Detection

RobustPeriod: Robust Time-Frequency Mining for Multiple Periodicity Detection

Forecasting

AutoAI-TS:AutoAI for Time Series Forecasting

2022

Classification

dCAM: Dimension-wise Class Activation Map for Explaining Multivariate Data Series Classification

Index

Scalable Time Series Compound Infrastructure

VLDB

2019

Representation Learning

GRAIL: Efficient Time-Series Representation Learning

Classification

Smile: A System to Support Machine Learning on EEG Data at Scale

2020

Database

Apache IoTDB: Time-series database for Internet of Things

Monarch: Google’s Planet-Scale In-Memory Time Series Database

Forecasting

DeepTRANS: A Deep Learning System for Public Bus Travel Time Estimation using Traffic Forecasting

2021

Imputation

ORBITS: Online Recovery of Missing Values in Multiple Time Series Streams

Forecasting

FlashP: An Analytical Pipeline for Real-time Forecasting of Time-Series Relational Data

Monitoring

Heracles: An Efficient Storage Model And Data Flushing For Performance Monitoring Timeseries

2022

Forecasting

METRO: A Generic Graph Neural Network Framework for Multivariate Time Series Forecasting AutoCTS: Automated Correlated Time Series Forecasting

Pattern Mining

Efficient Temporal Pattern Mining in Big Time Series Using Mutual Information NLC: Search Correlated Window Pairs on Long Time Series

Anomaly Detection

Unsupervised Time Series Outlier Detection with Diversity-Driven Convolutional Ensembles TranAD: Deep Transformer Networks for Anomaly Detection in Multivariate Time Series Data Anomaly Detection in Time Series: A Comprehensive Evaluation A New Distributional Treatment for Time Series and An Anomaly Detection Investigation TimeEval: A Benchmarking Toolkit for Time Series Anomaly Detection Algorithms

Decomposition

OnlineSTL: Scaling Time Series Decomposition by 100x Time Series Data Encoding for Efficient Storage: A Comparative Analysis in Apache IoTDB Chimp: Efficient Lossless Floating Point Compression for Time Series Databases

Imputation

On Repairing Timestamps for Regular Interval Time Series

Query

SENSOR: Data-driven Construction of Sketch-based Visual Query Interfaces for Time Series Data

Classification

FedTSC: A Secure Federated Learning System for Interpretable Time Series Classification

ICDE

2019

Indexing

TARDIS: Distributed Indexing Framework for Big Time Series Data

Imputation

Hankel Matrix Factorization for Tagged Time Series to Recover Missing Values During Blackouts

RecovDB: Accurate and Efficient Missing Blocks Recovery for Large Time Series

Correlation

Efficient Bottom-Up Discovery of Multi-scale Time Series Correlations Using Mutual Information

2020

Classification

Active Model Selection for Positive Unlabeled Time Series Classification

Mining

Neighbor Profile: Bagging Nearest Neighbors for Unsupervised Time Series Mining

Detection

Massively-Parallel Change Detection for Satellite Time Series Data with Missing Values

Anomaly Detection

User-driven Error Detection for Time Series with Events

Compression

Two-Level Data Compression using Machine Learning in Time Series Database

Forecasting

Telescope: An Automatic Feature Extraction and Transformation Approach for Seasonal Time Series Forecasting on a Level-Playing Field

Indexing

ChainLink: Indexing Big Time Series Data For Long Subsequence Matching

2021

Forecasting

EnhanceNet: Plugin Neural Networks for Enhancing Correlated Time Series Forecasting

An Actor-Critic Ensemble Aggregation Model for Time-Series Forecasting

Anomaly Detection

DAEMON: Unsupervised Anomaly Detection and Interpretation for Multivariate Time Series

Structure

Finding Time Series Natural Structures via A Novel Graph-Based Scheme

Classification

Efficient Shapelet Discovery for Time Series Classification

Correlated Dimensional

Scalable Model-Based Management of Correlated Dimensional Time Series in ModelarDB+

Database

TS-Benchmark: A Benchmark for Time Series Database

2022

Anomaly Detection

Robust and Explainable Autoencoders for Time Series Outlier Detection Anomaly Detection in Time Series with Robust Variational Quasi-Recurrent Autoencoders

Classification

IPS: Instance Profile for Shapelet Discovery for Time Series Classification Towards Backdoor Attack on Deep Learning based Time Series Classification Learning Evolvable Time-series Shapelets

Forecasting

Towards Spatio-Temporal Aware Traffic Time Series Forecasting

Index

Constructing Compact Time Series Index for Efficient Window Query Processing

KDD

2019

Forecasting

Modeling Extreme Events in Time Series Prediction

Multi-Horizon Time Series Forecasting with Temporal Attention Learning

Anomaly Detection

Robust Anomaly Detection for Multivariate Time Series through Stochastic Recurrent Neural Network

Time-Series Anomaly Detection Service at Microsoft

2020

Forecasting

Connecting the Dots: Multivariate Time Series Forecasting with Graph Neural Networks

Decomposition

Fast RobustSTL: Efficient and Robust Seasonal-Trend Decomposition for Time Series with Complex Patterns

Analysis

Matrix Profile XXI: A Geometric Approach to Time Series Chains Improves Robustness

Fitbit for Chickens? Time Series Data Mining Can Increase the Productivity of Poultry Farms

Weak Supervision

Multi-Source Deep Domain Adaptation with Weak Supervision for Time-Series Sensor Data

Forecasting

Attention based multi-modal new product sales time-series forecasting

Anomaly Detection

USAD: UnSupervised Anomaly Detection on multivariate time series

2021

Representation Learning

Representation Learning of Multivariate Time Series using a Transformer Framework

Forecasting

ST-Norm: Spatial and Temporal Normalization for Multi-variate Time Series Forecasting

Analysis

Statistical models coupling allows for complex localmultivariate time series analysis

Fast and Accurate Partial Fourier Transform for Time Series Data

Causal and Interpretable Rules for Time Series Analysis

Anomaly Detection

Multivariate Time Series Anomaly Detection and Interpretation using Hierarchical Inter-Metric and Temporal Embedding

Practical Approach to Asynchronous Multivariate Time Series Anomaly Detection and Localization

Time Series Anomaly Detection for Cyber-physical Systems via Neural System Identification and Bayesian Filtering

Classification

Apriori Convolutions for Highly Efficient and Accurate Time Series Classification

2022

Anomaly Detection

Scaling Time Series Anomaly Detection to Trillions of Datapoints and Ultra-fast Arriving Data Streams Local Evaluation of Time Series Anomaly Detection Algorithms

Forecasting

Learning the Evolutionary and Multi-scale Graph Structure for Multivariate Time Series Forecasting Multi-Variate Time Series Forecasting on Variable Subsets Learning to Rotate: Quaternion Transformer for Complicated Periodical Time Series Forecasting Pre-training Enhanced Spatial-temporal Graph Neural Network for Multivariate Time Series Forecasting

Representation Learning

ProActive: Self-Attentive Temporal Point Process Flows for Activity Sequences Learning Differential Operators for Interpretable Time Series Modeling

Classification

Non-stationary Time-aware Kernelized Attention for Temporal Event Prediction

ICDM

2019

Analysis

Discovering Subdimensional Motifs of Different Lengths in Large-Scale Multivariate Time Series

Matrix Profile XIX: Time Series Semantic Motifs: A New Primitive for Finding Higher-Level Structure in Time Series

Matrix Profile XVIII: Time Series Mining in the Face of Fast Moving Streams using a Learned Approximate Matrix Profile

Matrix Profile XV: Exploiting Time Series Consensus Motifs to Find Structure in Time Series Sets

A Wasserstein Subsequence Kernel for Time Series

Forecasting

MTEX-CNN: Multivariate Time Series EXplanations for Predictions with Convolutional Neural Networks

Classification

Triple-Shapelet Networks for Time Series Classification

2020

Analysis

Order-Preserving Metric Learning for Mining Multivariate Time Series

Matrix Profile XXII: Exact Discovery of Time Series Motifs under DTW

Inductive Granger Causal Modeling for Multivariate Time Series

Mining Recurring Patterns in Real-Valued Time Series using the Radius Profile

Learning Periods from Incomplete Multivariate Time Series

Anomaly Detection

Multivariate Time-series Anomaly Detection via Graph Attention Network

MERLIN: Parameter-Free Discovery of Arbitrary Length Anomalies in Massive Time Series Archives

Segmentation

Dual-Side Auto-Encoder for High-Dimensional Time Series Segmentation

Classification

Fast and Accurate Time Series Classification Through Supervised Interval Search

2021

Generating

Towards Generating Real-World Time Series Data

Continual Learning

Continual Learning for Multivariate Time Series Tasks with Variable Input Dimensions

Pattern Mining

Mining Statistically Significant Paths in Time Series Data from an Unknown Network Spikelet: An Adaptive Symbolic Approximation for Finding Higher-Level Structure in Time Series

Forecasting

SSDNet: State Space Decomposition Neural Network for Time Series Forecasting

Classification

Gaussian Process Model Learning for Time Series Classification Contrast Profile: A Novel Time Series Primitive that Allows Classification in Real World Settings LIFE: Learning Individual FEatures for Multivariate Time Series Prediction with Missing Values