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 2926–2950 of 6748 papers

TitleStatusHype
AutoML Meets Time Series Regression Design and Analysis of the AutoSeries ChallengeCode0
Snippet Policy Network for Multi-class Varied-length ECG Early Classification—0
Vision-Guided Forecasting -- Visual Context for Multi-Horizon Time Series Forecasting—0
Unsupervised Deep Anomaly Detection for Multi-Sensor Time-Series Signals—0
Trade When Opportunity Comes: Price Movement Forecasting via Locality-Aware Attention and Iterative Refinement Labeling—0
Inverse and Quanto Inverse Options in a Black-Scholes World—0
Massive feature extraction for explaining and foretelling hydroclimatic time series forecastability at the global scale—0
A Signal Detection Scheme Based on Deep Learning in OFDM Systems—0
Automatic Detection Of Noise Events at Shooting Range Using Machine Learning—0
COVID-19 and the gig economy in PolandCode0
Comparing Prophet and Deep Learning to ARIMA in Forecasting Wholesale Food Prices—0
Tsformer: Time series Transformer for tourism demand forecasting—0
Recovering lost and absent information in temporal networksCode0
FNetAR: Mixing Tokens with Autoregressive Fourier TransformsCode0
Neural Ordinary Differential Equation Model for Evolutionary Subspace Clustering and Its Applications—0
Dynamic functional time-series forecasts of foreign exchange implied volatility surfaces—0
A Framework for Imbalanced Time-series ForecastingCode0
Deep learning for temporal data representation in electronic health records: A systematic review of challenges and methodologies—0
Multiple species animal movements: network properties, disease dynamic and the impact of targeted control actionsCode0
Adaptive Inducing Points Selection For Gaussian Processes—0
High-dimensional Multivariate Time Series Forecasting in IoT Applications using Embedding Non-stationary Fuzzy Time Series—0
Approximation Theory of Convolutional Architectures for Time Series Modelling—0
Improving COVID-19 Forecasting using eXogenous VariablesCode0
OnlineSTL: Scaling Time Series Decomposition by 100x—0
Topological Attention for Time Series Forecasting—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