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

Showing 29513000 of 6748 papers

TitleStatusHype
Evaluation of deep learning models for multi-step ahead time series predictionCode1
Active multi-fidelity Bayesian online changepoint detectionCode1
Deep EHR Spotlight: a Framework and Mechanism to Highlight Events in Electronic Health Records for Explainable Predictions0
Measuring frequency-dependent selection in culture0
Intraday trading strategy based on time series and machine learning for Chinese stock market0
Isolating the impact of trading on grid frequency fluctuations0
An investigation of higher order moments of empirical financial data and the implications to risk0
Non-Compression Auto-Encoder for Detecting Road Surface Abnormality via Vehicle Driving NoiseCode0
Including Sparse Production Knowledge into Variational Autoencoders to Increase Anomaly Detection Reliability0
Reframing demand forecasting: a two-fold approach for lumpy and intermittent demand0
Recent Ice Trends in Swiss Mountain Lakes: 20-year Analysis of MODIS Imagery0
Cryptocurrency Dynamics: Rodeo or Ascot?0
Volume-Centred Range Bars: Novel Interpretable Representation of Financial Markets Designed for Machine Learning Applications0
Neural ODE ProcessesCode1
Domain Specific Concept Drift Detectors for Predicting Financial Time Series0
An Experimental Review on Deep Learning Architectures for Time Series ForecastingCode1
Handling Missing Observations with an RNN-based Prediction-Update Cycle0
Markov Modeling of Time-Series Data using Symbolic Analysis0
An Empirical Framework for Domain Generalization in Clinical SettingsCode1
Social Link Inference via Multi-View Matching Network from Spatio-Temporal Trajectories0
Graph Attention Recurrent Neural Networks for Correlated Time Series Forecasting -- Full version0
Joint Parameter Discovery and Generative Modeling of Dynamic SystemsCode0
Sparse Algorithms for Markovian Gaussian ProcessesCode0
Lossless compression with state space models using bits back codingCode0
Learning Time Series from Scale Information0
Learning Discriminative Prototypes with Dynamic Time WarpingCode1
An Efficient Method for the Classification of Croplands in Scarce-Label RegionsCode0
Temporal Cluster Matching for Change Detection of Structures from Satellite ImageryCode1
Do Word Embeddings Really Understand Loughran-McDonald's Polarities?0
Soft and subspace robust multivariate rank tests based on entropy regularized optimal transportCode0
Deep Time Series Models for Scarce Data0
Interpretable Feature Construction for Time Series Extrinsic Regression0
Tomography of time-dependent quantum spin networks with machine learning0
Modeling and forecasting Spread of COVID-19 epidemic in Iran until Sep 22, 2021, based on deep learning0
Hierarchical forecasting with a top-down alignment of independent level forecastsCode1
A machine learning approach to itinerary-level booking prediction in competitive airline markets0
Online Learning with Radial Basis Function Networks0
Double Articulation Analyzer with Prosody for Unsupervised Word and Phoneme DiscoveryCode0
A novel weighted approach for time series forecasting based on visibility graph0
Anticipating synchronization with machine learning0
Spectral Temporal Graph Neural Network for Multivariate Time-series ForecastingCode1
Modelling Animal Biodiversity Using Acoustic Monitoring and Deep Learning0
Visualising Deep Network's Time-Series Representations0
How to Train Your Flare Prediction Model: Revisiting Robust Sampling of Rare Events0
Spatiotemporal Tensor Completion for Improved Urban Traffic Imputation0
Affect2MM: Affective Analysis of Multimedia Content Using Emotion CausalityCode1
Estimating the causal effect of an intervention in a time series setting: the C-ARIMA approach0
Machine Learning Prediction of Time-Varying Rayleigh Channels0
Extension of the Lagrange multiplier test for error cross-section independence to large panels with non normal errors0
Streaming Linear System Identification with Reverse Experience Replay0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1naive classifierF187.47Unverified
2GRU-D - APC (n = 1)F127.3Unverified
3GRU-APC (n = 1)F125.7Unverified
4GRU-DF122.5Unverified
5GRUF122.3Unverified
6GRU-SimpleF122.2Unverified
7GRU-MeanF122.1Unverified
#ModelMetricClaimedVerifiedStatus
1SepTr% Test Accuracy98.51Unverified
2ViT% Test Accuracy98.11Unverified
3FlexTCN-4% Test Accuracy97.73Unverified
4MatchboxNet% Test Accuracy97.4Unverified
5CKCNN (100k)% Test Accuracy95.27Unverified
6FlexTCN-6% Test Accuracy (Raw Data)91.73Unverified
#ModelMetricClaimedVerifiedStatus
1ResBiLSTMMAE0.13Unverified