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 1726–1750 of 6748 papers

TitleStatusHype
Bioeconomic analysis of harvesting within a predator-prey system: A case study in the Chesapeake Bay fisheries—0
Fast fitting of neural ordinary differential equations by Bayesian neural gradient matching to infer ecological interactions from time series dataCode0
BayesLDM: A Domain-Specific Language for Probabilistic Modeling of Longitudinal Data—0
An Evaluation of Low Overhead Time Series Preprocessing Techniques for Downstream Machine Learning—0
Uncovering Regions of Maximum Dissimilarity on Random Process Data—0
A topological analysis of cointegrated data: a Z24 Bridge case study—0
Structured Recognition for Generative Models with Explaining AwayCode0
Modeling of Political Systems using Wasserstein Gradient Flows—0
Self-supervised Sequential Information Bottleneck for Robust Exploration in Deep Reinforcement Learning—0
Fairness in Forecasting of Observations of Linear Dynamical SystemsCode0
A new hazard event classification model via deep learning and multifractal—0
Testing the martingale difference hypothesis in high dimension—0
A Comparative Study on Unsupervised Anomaly Detection for Time Series: Experiments and Analysis—0
Deep Baseline Network for Time Series Modeling and Anomaly Detection—0
Symbolic Knowledge Extraction from Opaque Predictors Applied to Cosmic-Ray Data Gathered with LISA Pathfinder—0
Yes, DLGM! A novel hierarchical model for hazard classification—0
In-situ animal behavior classification using knowledge distillation and fixed-point quantization—0
Causal Modeling of Policy Interventions From Sequences of Treatments and Outcomes—0
Valuing Players Over Time—0
Assessing Lower Limb Strength using Internet-of-Things Enabled Chair—0
Reactmine: a statistical search algorithm for inferring chemical reactions from time series data—0
Modular Federated Learning—0
Causal discovery for time series with latent confoundersCode0
Spatiotemporal Cardiac Statistical Shape Modeling: A Data-Driven Approach—0
Impact analysis of recovery cases due to COVID19 using LSTM deep learning model—0
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All datasetsPhysioNet Challenge 2012Speech CommandsVentilator Pressure Prediction

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