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 5676–5700 of 6748 papers

TitleStatusHype
Rethinking Attention Mechanism in Time Series Classification—0
Rethinking the constraints of multimodal fusion: case study in Weakly-Supervised Audio-Visual Video Parsing—0
Retrieval Based Time Series Forecasting—0
Revealing hidden dynamics from time-series data by ODENet—0
Reverse Engineering Chemical Reaction Networks from Time Series Data—0
Review of automated time series forecasting pipelines—0
Review of Clustering Methods for Functional Data—0
Review of Data-centric Time Series Analysis from Sample, Feature, and Period—0
Improving COVID-19 Forecasting using eXogenous VariablesCode0
Improving Accuracy and Explainability of Online Handwriting RecognitionCode0
The Affine Wealth Model: An agent-based model of asset exchange that allows for negative-wealth agents and its empirical validationCode0
WaveletAE: A Wavelet-enhanced Autoencoder for Wind Turbine Blade Icing DetectionCode0
Real-time regression analysis with deep convolutional neural networksCode0
Nickell Bias in Panel Local Projection: Financial Crises Are Worse Than You ThinkCode0
Real Time Trajectory Prediction Using Deep Conditional Generative ModelsCode0
Improving Neural Networks for Time Series Forecasting using Data Augmentation and AutoMLCode0
Efficient Certified Training and Robustness Verification of Neural ODEsCode0
A case study of spatiotemporal forecasting techniques for weather forecastingCode0
Nested Multiple Instance Learning with Attention MechanismsCode0
Implementing spectral methods for hidden Markov models with real-valued emissionsCode0
Real-valued (Medical) Time Series Generation with Recurrent Conditional GANsCode0
The Area of the Convex Hull of Sampled Curves: a Robust Functional Statistical Depth MeasureCode0
Sparse Multi-Output Gaussian Processes for Medical Time Series PredictionCode0
A Capsule Network for Traffic Speed Prediction in Complex Road NetworksCode0
Anomaly Detection on Financial Time Series by Principal Component Analysis and Neural NetworksCode0
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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