SOTAVerified

Time Series Analysis

Time Series Analysis is a statistical technique used to analyze and model time-based data. It is used in various fields such as finance, economics, and engineering to analyze patterns and trends in data over time. The goal of time series analysis is to identify the underlying patterns, trends, and seasonality in the data, and to use this information to make informed predictions about future values.

( Image credit: Autoregressive CNNs for Asynchronous Time Series )

Papers

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Showing 3001–3050 of 6748 papers

TitleStatusHype
A Robust and Explainable Data-Driven Anomaly Detection Approach For Power Electronics—0
GT-GAN: General Purpose Time Series Synthesis with Generative Adversarial Networks—0
GTrans: Spatiotemporal Autoregressive Transformer with Graph Embeddings for Nowcasting Extreme Events—0
From Time Series to Euclidean Spaces: On Spatial Transformations for Temporal Clustering—0
From Text to Trends: A Unique Garden Analytics Perspective on the Future of Modern Agriculture—0
Guiding Visual Attention in Deep Convolutional Neural Networks Based on Human Eye Movements—0
Half-empty or half-full? A Hybrid Approach to Predict Recycling Behavior of Consumers to Increase Reverse Vending Machine Uptime—0
From Static to Dynamic Node Embeddings—0
Handling Missing Observations with an RNN-based Prediction-Update Cycle—0
Handling temporality of clinical events with application to Adverse Drug Event detection in Electronic Health Records: A scoping review—0
Handling Variable-Dimensional Time Series with Graph Neural Networks—0
Hankel low-rank approximation and completion in time series analysis and forecasting: a brief review—0
From sleep medicine to medicine during sleep: A clinical perspective—0
Happy or grumpy? A Machine Learning Approach to Analyze the Sentiment of Airline Passengers' Tweets—0
A Robust and Efficient Multi-Scale Seasonal-Trend Decomposition—0
Harnessing expressive capacity of Machine Learning modeling to represent complex coupling of Earth's auroral space weather regimes—0
From Rules to Regs: A Structural Topic Model of Collusion Research—0
From learning gait signatures of many individuals to reconstructing gait dynamics of one single individual—0
From Known to Unknown: Knowledge-guided Transformer for Time-Series Sales Forecasting in Alibaba—0
Concept-drifting Data Streams are Time Series; The Case for Continuous Adaptation—0
ArNet-ECG: Deep Learning for the Detection of Atrial Fibrillation from the Raw Electrocardiogram—0
A Model Combining Convolutional Neural Network and LightGBM Algorithm for Ultra-Short-Term Wind Power Forecasting—0
A Data-driven Market Simulator for Small Data Environments—0
Heat Demand Forecasting with Multi-Resolutional Representation of Heterogeneous Temporal Ensemble—0
AAMDRL: Augmented Asset Management with Deep Reinforcement Learning—0
Learning low-dimensional state embeddings and metastable clusters from time series data—0
Heterogeneous Neuronal and Synaptic Dynamics for Spike-Efficient Unsupervised Learning: Theory and Design Principles—0
Heterogeneous Relational Kernel Learning—0
Differential Recurrent Neural Network and its Application for Human Activity Recognition—0
From Images to Signals: Are Large Vision Models Useful for Time Series Analysis?—0
From Generalization Analysis to Optimization Designs for State Space Models—0
HFN: Heterogeneous Feature Network for Multivariate Time Series Anomaly Detection—0
Concentration inequalities for correlated network-valued processes with applications to community estimation and changepoint analysis—0
From FATS to feets: Further improvements to an astronomical feature extraction tool based on machine learning—0
Concealer: SGX-based Secure, Volume Hiding, and Verifiable Processing of Spatial Time-Series Datasets—0
From BOP to BOSS and Beyond: Time Series Classification with Dictionary Based Classifiers—0
Frequency-Domain Stochastic Modeling of Stationary Bivariate or Complex-Valued Signals—0
Frequency Domain Compact 3D Convolutional Neural Networks—0
Computer Model Calibration with Time Series Data using Deep Learning and Quantile Regression—0
Hierarchical Annotation for Building A Suite of Clinical Natural Language Processing Tasks: Progress Note Understanding—0
Arm order recognition in multi-armed bandit problem with laser chaos time series—0
A minor extension of the logistic equation for growth of word counts on online media: Parametric description of diversity of growth phenomena in society—0
Hierarchical Clustering for Smart Meter Electricity Loads based on Quantile Autocovariances—0
Hierarchical Clustering using Auto-encoded Compact Representation for Time-series Analysis—0
Hierarchical Deep Generative Models for Multi-Rate Multivariate Time Series—0
Hierarchical Estimation for Effective and Efficient Sampling Graph Neural Network—0
Frequency-based Multi Task learning With Attention Mechanism for Fault Detection In Power Systems—0
Free congruence: an exploration of expanded similarity measures for time series data—0
Hierarchical Graph Neural Networks for Causal Discovery and Root Cause Localization—0
Computer activity learning from system call time series—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1naive classifierF187.47—Unverified
2GRU-D - APC (n = 1)F127.3—Unverified
3GRU-APC (n = 1)F125.7—Unverified
4GRU-DF122.5—Unverified
5GRUF122.3—Unverified
6GRU-SimpleF122.2—Unverified
7GRU-MeanF122.1—Unverified
#ModelMetricClaimedVerifiedStatus
1SepTr% Test Accuracy98.51—Unverified
2ViT% Test Accuracy98.11—Unverified
3FlexTCN-4% Test Accuracy97.73—Unverified
4MatchboxNet% Test Accuracy97.4—Unverified
5CKCNN (100k)% Test Accuracy95.27—Unverified
6FlexTCN-6% Test Accuracy (Raw Data)91.73—Unverified
#ModelMetricClaimedVerifiedStatus
1ResBiLSTMMAE0.13—Unverified