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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 1251–1300 of 6748 papers

TitleStatusHype
AdaRNN: Adaptive Learning and Forecasting of Time SeriesCode0
A Review of Network Inference Techniques for Neural Activation Time SeriesCode0
Mitigating Data Redundancy to Revitalize Transformer-based Long-Term Time Series Forecasting SystemCode0
Geodesic Density Regression for Correcting 4DCT Pulmonary Respiratory Motion ArtifactsCode0
Fully Neural Network based Model for General Temporal Point ProcessesCode0
A Memory-Network Based Solution for Multivariate Time-Series ForecastingCode0
Fully Convolutional Network Bootstrapped by Word Encoding and Embedding for Activity Recognition in Smart HomesCode0
Fused-Lasso Regularized Cholesky Factors of Large Nonstationary Covariance Matrices of Longitudinal DataCode0
Frequentist Uncertainty in Recurrent Neural Networks via Blockwise Influence FunctionsCode0
Accurate Inference for Adaptive Linear ModelsCode0
A mathematical perspective on edge-centric brain functional connectivityCode0
Accurate Characterization of Non-Uniformly Sampled Time Series using Stochastic Differential EquationsCode0
Sequence Prediction using Spectral RNNsCode0
Forecasting with Multiple SeasonalityCode0
A Recurrent Neural Network Survival Model: Predicting Web User Return TimeCode0
Forecasting Time Series With Complex Seasonal Patterns Using Exponential SmoothingCode0
GAF-FusionNet: Multimodal ECG Analysis via Gramian Angular Fields and Split AttentionCode0
Gesture Recognition in RGB Videos UsingHuman Body Keypoints and Dynamic Time WarpingCode0
A machine learning framework for computationally expensive transient modelsCode0
Forecasting new diseases in low-data settings using transfer learningCode0
Forecasting COVID-19 Counts At A Single Hospital: A Hierarchical Bayesian ApproachCode0
Forecasting Precipitable Water Vapor Using LSTMsCode0
Forecasting Algorithms for Causal Inference with Panel DataCode0
Forecasting Across Time Series Databases using Recurrent Neural Networks on Groups of Similar Series: A Clustering ApproachCode0
Forecasting and Granger Modelling with Non-linear Dynamical DependenciesCode0
FNetAR: Mixing Tokens with Autoregressive Fourier TransformsCode0
Forecasting Brazilian and American COVID-19 cases based on artificial intelligence coupled with climatic exogenous variablesCode0
Coordination Event Detection and Initiator Identification in Time Series DataCode0
A projected nonlinear state-space model for forecasting time series signalsCode0
FLICU: A Federated Learning Workflow for Intensive Care Unit Mortality PredictionCode0
Adaptive pooling operators for weakly labeled sound event detectionCode0
A Probabilistic Autoencoder for Type Ia Supernovae Spectral Time SeriesCode0
Flipped Classroom: Effective Teaching for Time Series ForecastingCode0
SoQal: Selective Oracle Questioning for Consistency Based Active Learning of Cardiac SignalsCode0
A 1d convolutional network for leaf and time series classificationCode0
Fitting stochastic predator-prey models using both population density and kill rate dataCode0
Flow-based Spatio-Temporal Structured Prediction of Motion DynamicsCode0
Approximating Continuous Functions on Persistence Diagrams Using Template FunctionsCode0
Few-shot human motion prediction for heterogeneous sensorsCode0
Clustering Noisy Signals with Structured Sparsity Using Time-Frequency RepresentationCode0
Clustering Market Regimes using the Wasserstein DistanceCode0
A log-linear time algorithm for constrained changepoint detectionCode0
DMS, AE, DAA: methods and applications of adaptive time series model selection, ensemble, and financial evaluationCode0
Approximate Bayesian Computation with Path SignaturesCode0
fETSmcs: Feature-based ETS model component selectionCode0
Feature Selection on a Flare Forecasting Testbed: A Comparative Study of 24 MethodsCode0
Feature Selection for Multivariate Time Series via Network PruningCode0
Feature engineering workflow for activity recognition from synchronized inertial measurement unitsCode0
Feature space approximation for kernel-based supervised learningCode0
Fast Online Deconvolution of Calcium Imaging DataCode0
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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