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 3951–3975 of 6748 papers

TitleStatusHype
Topological EEG Nonlinear Dynamics Analysis for Emotion Recognition—0
Topological Feature Vectors for Chatter Detection in Turning Processes—0
Topological Hidden Markov Models—0
Topological Representational Similarity Analysis in Brains and Beyond—0
Topological Signal Processing using the Weighted Ordinal Partition Network—0
Topology-based Clusterwise Regression for User Segmentation and Demand Forecasting—0
Topology, Convergence, and Reconstruction of Predictive States—0
Topology data analysis of critical transitions in financial networks—0
Topology Identification under Spatially Correlated Noise—0
To Post or Not to Post: Using Online Trends to Predict Popularity of Offline Content—0
TOTOPO: Classifying univariate and multivariate time series with Topological Data Analysis—0
To VaR, or Not to VaR, That is the Question—0
Toward a generic representation of random variables for machine learning—0
Towards Accurate Predictions and Causal 'What-if' Analyses for Planning and Policy-making: A Case Study in Emergency Medical Services Demand—0
Towards a Computational Framework for Automated Discovery and Modeling of Biological Rhythms from Wearable Data Streams—0
Towards a Design Framework for TNN-Based Neuromorphic Sensory Processing Units—0
Towards a Kernel based Uncertainty Decomposition Framework for Data and Models—0
Towards an AI-based Early Warning System for Bridge Scour—0
Towards a Near Universal Time Series Data Mining Tool: Introducing the Matrix Profile—0
Towards a Rigorous Evaluation of Explainability for Multivariate Time Series—0
Towards a Rigorous Evaluation of XAI Methods on Time Series—0
Towards a text analysis system for political debates—0
Towards a universal neural network encoder for time series—0
Towards automated symptoms assessment in mental health—0
Towards Better Long-range Time Series Forecasting using Generative Adversarial Networks—0
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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