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 201–250 of 6748 papers

TitleStatusHype
Spatial, Temporal, and Geometric Fusion for Remote Sensing Images—0
Assessing the Potential of AI for Spatially Sensitive Nature-Related Financial Risks—0
Evaluating Large Language Models on Time Series Feature Understanding: A Comprehensive Taxonomy and Benchmark—0
Review of Data-centric Time Series Analysis from Sample, Feature, and Period—0
Mamba-360: Survey of State Space Models as Transformer Alternative for Long Sequence Modelling: Methods, Applications, and ChallengesCode2
TimeCSL: Unsupervised Contrastive Learning of General Shapelets for Explorable Time Series Analysis—0
Deep Learning for Satellite Image Time Series Analysis: A Review—0
Log-PDE Methods for Rough Signature Kernels—0
A Survey on Hypergraph Neural Networks: An In-Depth and Step-By-Step Guide—0
Heracles: A Hybrid SSM-Transformer Model for High-Resolution Image and Time-Series AnalysisCode1
A Survey on State-of-the-art Deep Learning Applications and Challenges—0
A data-informed mathematical model of microglial cell dynamics during ischemic stroke in the middle cerebral artery—0
Foundation Models for Time Series Analysis: A Tutorial and SurveyCode7
Capsule Neural Networks as Noise Stabilizer for Time Series Data—0
Decoding Multilingual Topic Dynamics and Trend Identification through ARIMA Time Series Analysis on Social Networks: A Novel Data Translation Framework Enhanced by LDA/HDP Models—0
Advancing multivariate time series similarity assessment: an integrated computational approach—0
Self-Supervised Learning for Time Series: Contrastive or Generative?Code1
Caformer: Rethinking Time Series Analysis from Causal Perspective—0
Time Series Analysis of Key Societal Events as Reflected in Complex Social Media Data Streams—0
Exploring the Influence of Dimensionality Reduction on Anomaly Detection Performance in Multivariate Time SeriesCode0
ConvTimeNet: A Deep Hierarchical Fully Convolutional Model for Multivariate Time Series AnalysisCode0
Equipment Health Assessment: Time Series Analysis for Wind Turbine Performance—0
Time Series Analysis in Compressor-Based Machines: A Survey—0
TOTEM: TOkenized Time Series EMbeddings for General Time Series AnalysisCode3
IMUOptimize: A Data-Driven Approach to Optimal IMU Placement for Human Pose Estimation with Transformer Architecture—0
Incorporating Taylor Series and Recursive Structure in Neural Networks for Time Series Prediction—0
MTSA-SNN: A Multi-modal Time Series Analysis Model Based on Spiking Neural NetworkCode1
Sparse-VQ Transformer: An FFN-Free Framework with Vector Quantization for Enhanced Time Series Forecasting—0
Multi-Patch Prediction: Adapting LLMs for Time Series Representation LearningCode2
Deep Learning for Multivariate Time Series Imputation: A SurveyCode3
MOMENT: A Family of Open Time-series Foundation ModelsCode2
Assessing the Impact of Distribution Shift on Reinforcement Learning Performance—0
Empowering Time Series Analysis with Large Language Models: A Survey—0
Multi-scale fMRI time series analysis for understanding neurodegeneration in MCI—0
Position: What Can Large Language Models Tell Us about Time Series AnalysisCode2
Timer: Generative Pre-trained Transformers Are Large Time Series ModelsCode4
Minusformer: Improving Time Series Forecasting by Progressively Learning ResidualsCode2
Efficient Market Dynamics: Unraveling Informational Efficiency in UK Horse Racing Betting Markets Through Betfair's Time Series Analysis—0
Large Language Models for Time Series: A SurveyCode4
Conditioning non-linear and infinite-dimensional diffusion processesCode0
Distillation Enhanced Time Series Forecasting Network with Momentum Contrastive LearningCode0
Efficient Observation Time Window Segmentation for Administrative Data Machine Learning—0
TNANet: A Temporal-Noise-Aware Neural Network for Suicidal Ideation Prediction with Noisy Physiological Data—0
Parsimony or Capability? Decomposition Delivers Both in Long-term Time Series Forecasting—0
Spatial-Temporal Large Language Model for Traffic PredictionCode2
Machine learning approach to detect dynamical states from recurrence measures—0
PatchAD: A Lightweight Patch-based MLP-Mixer for Time Series Anomaly DetectionCode1
ModernTCN: A Modern Pure Convolution Structure for General Time Series AnalysisCode3
DualDynamics: Synergizing Implicit and Explicit Methods for Robust Irregular Time Series AnalysisCode1
The Rise of Diffusion Models in Time-Series ForecastingCode3
Show:102550
← PrevPage 5 of 135Next →
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