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 4651–4675 of 6748 papers

TitleStatusHype
Large-Scale Characterization and Segmentation of Internet Path Delays with Infinite HMMsCode0
Input-Cell Attention Reduces Vanishing Saliency of Recurrent Neural NetworksCode0
Deep Learning for Plasma Tomography and Disruption Prediction from Bolometer Data—0
Causal inference for climate change events from satellite image time series using computer vision and deep learning—0
Textual Data for Time Series Forecasting—0
Time Series Vector Autoregression Prediction of the Ecological Footprint based on Energy Parameters—0
High dimensional regression for regenerative time-series: an application to road traffic modelingCode0
Inference of Binary Regime Models with Jump Discontinuities—0
MLAT: Metric Learning for kNN in Streaming Time Series—0
Winning the ICCV 2019 Learning to Drive Challenge—0
Critical Transitions in Intensive Care Units: A Sepsis Case Study—0
Wasserstein total variation filtering—0
Self-attention for raw optical Satellite Time Series ClassificationCode0
Study of the impact of climate change on precipitation in Paris area using method based on iterative multiscale dynamic time warping (IMS-DTW)—0
Collapsed Amortized Variational Inference for Switching Nonlinear Dynamical Systems—0
Generalised learning of time-series: Ornstein-Uhlenbeck processes—0
Entropic Dynamic Time Warping Kernels for Co-evolving Financial Time Series Analysis—0
Order patterns, their variation and change points in financial time series and Brownian motion—0
Content Removal as a Moderation Strategy: Compliance and Other Outcomes in the ChangeMyView Community—0
You May Not Need Order in Time Series Forecasting—0
GesturePod: Enabling On-device Gesture-based Interaction for White Cane Users—0
Temporal Network Sampling—0
Coupling Oceanic Observation Systems to Study Mesoscale Ocean DynamicsCode0
Forecasting under Long Memory and Nonstationarity—0
Deep Amortized Variational Inference for Multivariate Time Series Imputation with Latent Gaussian Process Models—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