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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 3001–3025 of 6748 papers

TitleStatusHype
From learning gait signatures of many individuals to reconstructing gait dynamics of one single individual—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 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
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
ArNet-ECG: Deep Learning for the Detection of Atrial Fibrillation from the Raw Electrocardiogram—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
A Model Combining Convolutional Neural Network and LightGBM Algorithm for Ultra-Short-Term Wind Power Forecasting—0
Happy or grumpy? A Machine Learning Approach to Analyze the Sentiment of Airline Passengers' Tweets—0
A Data-driven Market Simulator for Small Data Environments—0
Harnessing expressive capacity of Machine Learning modeling to represent complex coupling of Earth's auroral space weather regimes—0
AAMDRL: Augmented Asset Management with Deep Reinforcement Learning—0
Learning low-dimensional state embeddings and metastable clusters from time series data—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
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
Heat Demand Forecasting with Multi-Resolutional Representation of Heterogeneous Temporal Ensemble—0
Concealer: SGX-based Secure, Volume Hiding, and Verifiable Processing of Spatial Time-Series Datasets—0
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All datasetsPhysioNet Challenge 2012Speech CommandsVentilator Pressure Prediction

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