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 701–725 of 6748 papers

TitleStatusHype
Learning Differential Equations that are Easy to SolveCode1
CANShield: Deep Learning-Based Intrusion Detection Framework for Controller Area Networks at the Signal-LevelCode1
Causal structure learning from time series: Large regression coefficients may predict causal links better in practice than small p-valuesCode1
Learning Linear Dynamical Systems via Spectral FilteringCode1
Learning Signal Temporal Logic through Neural Network for Interpretable ClassificationCode1
Learning Task-Aware Effective Brain Connectivity for fMRI Analysis with Graph Neural NetworksCode1
Learning the spatio-temporal relationship between wind and significant wave height using deep learningCode1
TS2Vec: Towards Universal Representation of Time SeriesCode1
Color-aware two-branch DCNN for efficient plant disease classificationCode1
Legendre Memory Units: Continuous-Time Representation in Recurrent Neural NetworksCode1
LightTS: Lightweight Time Series Classification with Adaptive Ensemble Distillation -- Extended VersionCode1
Lightweight Neural Architecture Search for Temporal Convolutional Networks at the EdgeCode1
CALDA: Improving Multi-Source Time Series Domain Adaptation with Contrastive Adversarial LearningCode1
Building Calibrated Deep Models via Uncertainty Matching with Auxiliary Interval PredictorsCode1
Calibrated One-class Classification for Unsupervised Time Series Anomaly DetectionCode1
Local Evaluation of Time Series Anomaly Detection AlgorithmsCode1
Logsig-RNN: a novel network for robust and efficient skeleton-based action recognitionCode1
Long Expressive Memory for Sequence ModelingCode1
BolT: Fused Window Transformers for fMRI Time Series AnalysisCode1
Bilinear Input Normalization for Neural Networks in Financial ForecastingCode1
A semi-supervised methodology for fishing activity detection using the geometry behind the trajectory of multiple vesselsCode1
A Sentinel-2 multi-year, multi-country benchmark dataset for crop classification and segmentation with deep learningCode1
Machine Learning Panel Data Regressions with Heavy-tailed Dependent Data: Theory and ApplicationCode1
Machine Learning Time Series Regressions with an Application to NowcastingCode1
Building an Automated and Self-Aware Anomaly Detection SystemCode1
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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