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 3001–3050 of 6748 papers

TitleStatusHype
MissFormer: (In-)attention-based handling of missing observations for trajectory filtering and prediction—0
National-scale electricity peak load forecasting: Traditional, machine learning, or hybrid model?—0
Long Short-term Cognitive NetworksCode0
Attaining entropy production and dissipation maps from Brownian movies via neural networksCode0
As easy as APC: overcoming missing data and class imbalance in time series with self-supervised learningCode0
FallDeF5: A Fall Detection Framework Using 5G-based Deep Gated Recurrent Unit Networks—0
Evolving-Graph Gaussian ProcessesCode0
Improved Prediction and Network Estimation Using the Monotone Single Index Multi-variate Autoregressive Model—0
False Negative Reduction in Video Instance Segmentation using Uncertainty EstimatesCode0
Capturing the temporal constraints of gradual patternsCode0
On a novel training algorithm for sequence-to-sequence predictive recurrent networks—0
Autonomous Deep Quality Monitoring in Streaming EnvironmentsCode0
Functional Classwise Principal Component Analysis: A Novel Classification Framework—0
The mbsts package: Multivariate Bayesian Structural Time Series Models in R—0
Bayesian Inference in High-Dimensional Time-Serieswith the Orthogonal Stochastic Linear Mixing Model—0
Condition Monitoring of Drive Trains by Data Fusion of Acoustic Emission and Vibration SensorsCode0
Temporal Graph Signal Decomposition—0
Neural ODE to model and prognose thermoacoustic instability—0
Domain-guided Machine Learning for Remotely Sensed In-Season Crop Growth Estimation—0
Beyond Predictions in Neural ODEs: Identification and Interventions—0
Machine learning structure preserving brackets for forecasting irreversible processes—0
Approximate Bayesian Computation with Path SignaturesCode0
MegazordNet: combining statistical and machine learning standpoints for time series forecasting—0
Innovations Autoencoder and its Application in One-class Anomalous Sequence Detection—0
Serial-EMD: Fast Empirical Mode Decomposition Method for Multi-dimensional Signals Based on Serialization—0
Residual Networks as Flows of Velocity Fields for Diffeomorphic Time Series Alignment—0
Spliced Binned-Pareto Distribution for Robust Modeling of Heavy-tailed Time SeriesCode0
Attention-based Neural Network for Driving Environment Complexity Perception—0
A mathematical perspective on edge-centric brain functional connectivityCode0
Experimentally testable whole brain manifolds that recapitulate behavior—0
Progressive Modality Reinforcement for Human Multimodal Emotion Recognition From Unaligned Multimodal Sequences—0
On the benefits of maximum likelihood estimation for Regression and Forecasting—0
Combining Pseudo-Point and State Space Approximations for Sum-Separable Gaussian ProcessesCode0
Minimax Estimation of Partially-Observed Vector AutoRegressionsCode0
Pre-treatment of outliers and anomalies in plant data: Methodology and case study of a Vacuum Distillation Unit—0
Multi-Modal Prototype Learning for Interpretable Multivariable Time Series Classification—0
Adaptive Visibility Graph Neural Network and It's Application in Modulation Classification—0
Deep Neural Networks for Approximating Stream Reasoning with C-SPARQL—0
Adversarial Attacks on Deep Models for Financial Transaction RecordsCode0
A stochastic metapopulation state-space approach to modeling and estimating Covid-19 spread—0
Faster than LASER -- Towards Stream Reasoning with Deep Neural Networks—0
Cine-MRI detection of abdominal adhesions with spatio-temporal deep learning—0
Economic Nowcasting with Long Short-Term Memory Artificial Neural Networks (LSTM)—0
Trend-Following Strategies via Dynamic Momentum Learning—0
Differentiable Neural Architecture Search with Morphism-based Transformable Backbone Architectures—0
Signal processing on simplicial complexes—0
A Two-Step Framework for Arbitrage-Free Prediction of the Implied Volatility Surface—0
A Self-Supervised Framework for Function Learning and Extrapolation—0
Hierarchically Regularized Deep Forecasting—0
EuroCrops: A Pan-European Dataset for Time Series Crop Type Classification—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