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 1551–1575 of 6748 papers

TitleStatusHype
Benign Overfitting in Time Series Linear Models with Over-Parameterization—0
STONet: A Neural-Operator-Driven Spatio-temporal Network—0
Multi-scale Anomaly Detection for Big Time Series of Industrial Sensors—0
Time Series Clustering for Grouping Products Based on Price and Sales Patterns—0
Probabilistic Charging Power Forecast of EVCS: Reinforcement Learning Assisted Deep Learning Approach—0
Assessing Differentially Private Variational Autoencoders under Membership InferenceCode0
Nonparametric Analysis of Dynamic Random Utility Models—0
EvoSTS Forecasting: Evolutionary Sparse Time-Series Forecasting—0
Learning Probability Distributions in Macroeconomics and Finance—0
Time Series of Non-Additive Metrics: Identification and Interpretation of Contributing Factors of Variance by Linear Decomposition—0
LSTM-Autoencoder based Anomaly Detection for Indoor Air Quality Time Series DataCode1
Stability of China's Stock Market: Measure and Forecast by Ricci Curvature on Network—0
The multi-modal universe of fast-fashion: the Visuelle 2.0 benchmarkCode1
Neural Topic Modeling of Psychotherapy Sessions—0
Investigating Temporal Convolutional Neural Networks for Satellite Image Time Series Classification: A survey—0
Features of the Earth's seasonal hydroclimate: Characterizations and comparisons across the Koppen-Geiger climates and across continents—0
Time series features for supporting hydrometeorological explorations and predictions in ungauged locations using large datasets—0
A quantum generative model for multi-dimensional time series using Hamiltonian learning—0
SRMD: Sparse Random Mode DecompositionCode0
Surrogate Ensemble Forecasting for Dynamic Climate Impact Models—0
Deep Normed Embeddings for Patient RepresentationCode0
A self-paced BCI system with low latency for motor imagery onset detection based on time series prediction paradigm—0
Variational Heteroscedastic Volatility ModelCode0
Lyapunov-Guided Representation of Recurrent Neural Network PerformanceCode0
Transfer Learning for Autonomous Chatter Detection in Machining—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