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 11011125 of 6748 papers

TitleStatusHype
HigeNet: A Highly Efficient Modeling for Long Sequence Time Series Prediction in AIOpsCode0
High-Dimensional Multivariate Forecasting with Low-Rank Gaussian Copula ProcessesCode0
A Transformer Framework for Data Fusion and Multi-Task Learning in Smart CitiesCode0
A Distance for HMMs based on Aggregated Wasserstein Metric and State RegistrationCode0
Hierarchical Probabilistic Model for Blind Source Separation via Legendre TransformationCode0
High dimensional regression for regenerative time-series: an application to road traffic modelingCode0
Hide-and-Seek Privacy ChallengeCode0
Hierarchical Attention-Based Recurrent Highway Networks for Time Series PredictionCode0
A Comparative Study of Gamma Markov Chains for Temporal Non-Negative Matrix FactorizationCode0
Hidden Parameter Recurrent State Space Models For Changing Dynamics ScenariosCode0
High-dimensional regression with potential prior information on variable importanceCode0
Harnessing the power of Topological Data Analysis to detect change points in time seriesCode0
A toolkit for data-driven discovery of governing equations in high-noise regimesCode0
Guiding Sentiment Analysis with Hierarchical Text Clustering: Analyzing the German X/Twitter Discourse on Face Masks in the 2020 COVID-19 PandemicCode0
Half-sibling regression meets exoplanet imaging: PSF modeling and subtraction using a flexible, domain knowledge-driven, causal frameworkCode0
Anamnesic Neural Differential Equations with Orthogonal Polynomial ProjectionsCode0
GTEA: Inductive Representation Learning on Temporal Interaction Graphs via Temporal Edge AggregationCode0
Guidelines for Augmentation Selection in Contrastive Learning for Time Series ClassificationCode0
HERMES: Hybrid Error-corrector Model with inclusion of External Signals for nonstationary fashion time seriesCode0
Analyzing Linear Dynamical Systems: From Modeling to Coding and LearningCode0
Graph Edit NetworksCode0
Graph-based Knowledge Tracing: Modeling Student Proficiency Using Graph Neural NetworkCode0
Graph Gamma Process Generalized Linear Dynamical SystemsCode0
Gradient-free training of recurrent neural networksCode0
Analyzing Dynamical Brain Functional Connectivity As Trajectories on Space of Covariance MatricesCode0
Show:102550
← PrevPage 45 of 270Next →

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