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 55015550 of 6748 papers

TitleStatusHype
Recurrent Auto-Encoder Model for Large-Scale Industrial Sensor Signal AnalysisCode0
Thresholded ConvNet Ensembles: Neural Networks for Technical Forecasting0
Process Monitoring Using Maximum Sequence Divergence0
Learning The Sequential Temporal Information with Recurrent Neural Networks0
A Variational Time Series Feature Extractor for Action PredictionCode0
Transfer Learning for Clinical Time Series Analysis using Recurrent Neural Networks0
Mining Illegal Insider Trading of Stocks: A Proactive Approach0
Dynamic Prediction Length for Time Series with Sequence to Sequence Networks0
Robust and Scalable Models of Microbiome Dynamics0
Deep Bayesian Nonparametric Tracking0
Accurate Uncertainties for Deep Learning Using Calibrated RegressionCode0
Hierarchical Deep Generative Models for Multi-Rate Multivariate Time Series0
Stock Movement Prediction from Tweets and Historical PricesCode0
Improving Optimization in Models With Continuous Symmetry Breaking0
Sampling and Reconstruction of Signals on Product GraphsCode0
An Introduction to Animal Movement Modeling with Hidden Markov Models using Stan for Bayesian Inference0
Nonlinearity in stock networks0
Multilevel Wavelet Decomposition Network for Interpretable Time Series AnalysisCode0
Focusing on What is Relevant: Time-Series Learning and Understanding using Attention0
Complex Gated Recurrent Neural NetworksCode0
What Makes An Asset Useful?0
A Review of Network Inference Techniques for Neural Activation Time SeriesCode0
Kernel Methods for Nonlinear Connectivity Detection0
Multi-variable LSTM neural network for autoregressive exogenous model0
Denoising Time Series Data Using Asymmetric Generative Adversarial Networks0
Deep Learning with Convolutional Neural Network for Objective Skill Evaluation in Robot-assisted Surgery0
A review on distance based time series classification0
The Role of Agricultural Sector Productivity in Economic Growth: The Case of Iran's Economic Development Plan0
Stationary Geometric Graphical Model Selection0
Discovering Signals from Web Sources to Predict Cyber Attacks0
SOM-VAE: Interpretable Discrete Representation Learning on Time SeriesCode0
EigenNetworks0
History Playground: A Tool for Discovering Temporal Trends in Massive Textual Corpora0
Hierarchical Attention-Based Recurrent Highway Networks for Time Series PredictionCode0
Quantifying the dynamics of topical fluctuations in languageCode0
Deep Neural Models of Semantic Shift0
Sea surface temperature prediction and reconstruction using patch-level neural network representations0
RiskFinder: A Sentence-level Risk Detector for Financial Reports0
Jerk-Aware Video Acceleration Magnification0
Metric on Nonlinear Dynamical Systems with Perron-Frobenius OperatorsCode0
Root-cause Analysis for Time-series Anomalies via Spatiotemporal Graphical Modeling in Distributed Complex Systems0
Predicting County Level Corn Yields Using Deep Long Short Term Memory Models0
Unsupervised detection of diachronic word sense evolution0
Currency exchange prediction using machine learning, genetic algorithms and technical analysis0
Adversarial Constraint Learning for Structured PredictionCode0
BRITS: Bidirectional Recurrent Imputation for Time SeriesCode0
Statistical properties and multifractality of Bitcoin0
Multivariate Convolutional Sparse Coding for Electromagnetic Brain SignalsCode0
Learning Nonlinear Brain Dynamics: van der Pol Meets LSTM0
Structure Learning from Time Series with False Discovery Control0
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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