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 26012650 of 6748 papers

TitleStatusHype
Forecasting Thermoacoustic Instabilities in Liquid Propellant Rocket Engines Using Multimodal Bayesian Deep Learning0
Online learning of windmill time series using Long Short-term Cognitive Networks0
Explainable nonlinear modelling of multiple time series with invertible neural networks0
National-scale electricity peak load forecasting: Traditional, machine learning, or hybrid model?0
Market regime classification with signaturesCode1
Long Short-term Cognitive NetworksCode0
MissFormer: (In-)attention-based handling of missing observations for trajectory filtering and prediction0
Attaining entropy production and dissipation maps from Brownian movies via neural networksCode0
Continuous Latent Process FlowsCode1
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 Networks0
Evolving-Graph Gaussian ProcessesCode0
False Negative Reduction in Video Instance Segmentation using Uncertainty EstimatesCode0
Improved Prediction and Network Estimation Using the Monotone Single Index Multi-variate Autoregressive Model0
Capturing the temporal constraints of gradual patternsCode0
On a novel training algorithm for sequence-to-sequence predictive recurrent networks0
Autonomous Deep Quality Monitoring in Streaming EnvironmentsCode0
Automated Evolutionary Approach for the Design of Composite Machine Learning PipelinesCode1
Time-Series Representation Learning via Temporal and Contextual ContrastingCode1
Functional Classwise Principal Component Analysis: A Novel Classification Framework0
The mbsts package: Multivariate Bayesian Structural Time Series Models in R0
Accelerating Recurrent Neural Networks for Gravitational Wave ExperimentsCode1
Condition Monitoring of Drive Trains by Data Fusion of Acoustic Emission and Vibration SensorsCode0
Closed-form Continuous-time Neural ModelsCode2
Bayesian Inference in High-Dimensional Time-Serieswith the Orthogonal Stochastic Linear Mixing Model0
Temporal Graph Signal Decomposition0
Autoformer: Decomposition Transformers with Auto-Correlation for Long-Term Series ForecastingCode2
Neural ODE to model and prognose thermoacoustic instability0
Domain-guided Machine Learning for Remotely Sensed In-Season Crop Growth Estimation0
MegazordNet: combining statistical and machine learning standpoints for time series forecasting0
Beyond Predictions in Neural ODEs: Identification and Interventions0
Innovations Autoencoder and its Application in One-class Anomalous Sequence Detection0
Continuous-Time Deep Glioma Growth ModelsCode1
Machine learning structure preserving brackets for forecasting irreversible processes0
Spatio-Temporal SAR-Optical Data Fusion for Cloud Removal via a Deep Hierarchical ModelCode1
Unsupervised Speech Enhancement using Dynamical Variational Auto-EncodersCode1
Approximate Bayesian Computation with Path SignaturesCode0
STRESS: Super-Resolution for Dynamic Fetal MRI using Self-Supervised LearningCode1
Serial-EMD: Fast Empirical Mode Decomposition Method for Multi-dimensional Signals Based on Serialization0
Residual Networks as Flows of Velocity Fields for Diffeomorphic Time Series Alignment0
Spliced Binned-Pareto Distribution for Robust Modeling of Heavy-tailed Time SeriesCode0
Attention-based Neural Network for Driving Environment Complexity Perception0
Neural Controlled Differential Equations for Online Prediction TasksCode1
A mathematical perspective on edge-centric brain functional connectivityCode0
Experimentally testable whole brain manifolds that recapitulate behavior0
Progressive Modality Reinforcement for Human Multimodal Emotion Recognition From Unaligned Multimodal Sequences0
GPLA-12: An Acoustic Signal Dataset of Gas Pipeline LeakageCode1
TS2Vec: Towards Universal Representation of Time SeriesCode1
pyWATTS: Python Workflow Automation Tool for Time SeriesCode1
Combining Pseudo-Point and State Space Approximations for Sum-Separable Gaussian ProcessesCode0
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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