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 58515900 of 6748 papers

TitleStatusHype
Discovering Playing Patterns: Time Series Clustering of Free-To-Play Game Data0
Forecasting Player Behavioral Data and Simulating in-Game Events0
Multifractal analysis of the time series of daily means of wind speed in complex regions0
Indexing the Event Calculus with Kd-trees to Monitor Diabetes0
Learning Predictive Leading Indicators for Forecasting Time Series Systems with Unknown Clusters of Forecast TasksCode0
Classification of Time-Series Images Using Deep Convolutional Neural NetworksCode0
DeepTFP: Mobile Time Series Data Analytics based Traffic Flow PredictionCode0
Wikipedia graph mining: dynamic structure of collective memoryCode0
Comparison of PCA with ICA from data distribution perspective0
Model-free prediction of noisy chaotic time series by deep learning0
Learning the Exact Topology of Undirected Consensus Networks0
Symbolic Analysis-based Reduced Order Markov Modeling of Time Series Data0
Catching Anomalous Distributed Photovoltaics: An Edge-based Multi-modal Anomaly Detection0
Automatic Error Analysis of Human Motor Performance for Interactive Coaching in Virtual Reality0
House Price Prediction Using LSTM0
When Traffic Flow Prediction Meets Wireless Big Data Analytics0
Feature-based time-series analysis0
Cross-modal Recurrent Models for Weight Objective Prediction from Multimodal Time-series Data0
Deep-Learnt Classification of Light CurvesCode0
A textual transform of multivariate time-series for prognostics0
Nonnegative matrix factorization with side information for time series recovery and prediction0
Kinetic theory and Brazilian income distribution0
Social Style Characterization from Egocentric Photo-streams0
A new approach to the modeling of financial volumes0
Granger Mediation Analysis of Multiple Time Series with an Application to fMRI0
Anomaly Detection for a Water Treatment System Using Unsupervised Machine Learning0
Motif-based Rule Discovery for Predicting Real-valued Time Series0
On Early-stage Debunking Rumors on Twitter: Leveraging the Wisdom of Weak Learners0
Discovering Potential Correlations via Hypercontractivity0
Cascaded Region-based Densely Connected Network for Event Detection: A Seismic Application0
Extracting Traffic Primitives Directly from Naturalistically Logged Data for Self-Driving Applications0
Support Spinor Machine0
R2N2: Residual Recurrent Neural Networks for Multivariate Time Series Forecasting0
Basic Filters for Convolutional Neural Networks Applied to Music: Training or Design?0
RNN-based Early Cyber-Attack Detection for the Tennessee Eastman Process0
Tensor Representation in High-Frequency Financial Data for Price Change Prediction0
Towards social pattern characterization in egocentric photo-streams0
Boosting the kernelized shapelets: Theory and algorithms for local features0
Predicting Remaining Useful Life using Time Series Embeddings based on Recurrent Neural Networks0
Boosting Information Extraction Systems with Character-level Neural Networks and Free Noisy Supervision0
Forecasting Consumer Spending from Purchase Intentions Expressed on Social Media0
Classifying Frames at the Sentence Level in News Articles0
A State-Space Approach to Dynamic Nonnegative Matrix Factorization0
Can Agent-Based Models Probe Market Microstructure?0
Interpretable Categorization of Heterogeneous Time Series Data0
On the Reconstruction Risk of Convolutional Sparse Dictionary LearningCode0
m-TSNE: A Framework for Visualizing High-Dimensional Multivariate Time Series0
Explainable Recommendation: Theory and Applications0
Boltzmann machines for time-series0
An Improved Multi-Output Gaussian Process RNN with Real-Time Validation for Early Sepsis Detection0
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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