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 48014850 of 6748 papers

TitleStatusHype
Urban Traffic Prediction from Spatio-Temporal Data Using Deep Meta LearningCode0
Robust Anomaly Detection for Multivariate Time Series through Stochastic Recurrent Neural NetworkCode0
Interpretable Classification of Time-Series Data using Efficient Enumerative Techniques0
Deep Generative Quantile-Copula Models for Probabilistic Forecasting0
Recurrent Neural Networks: An Embedded Computing Perspective0
Time Series Analysis of Electricity Price and Demand to Find Cyber-attacks using Stationary Analysis0
A Neural Network-Based On-device Learning Anomaly Detector for Edge Devices0
Trading via Image ClassificationCode0
TSRuleGrowth : Extraction de règles de prédiction semi-ordonnées à partir d'une série temporelle d'éléments discrets, application dans un contexte d'intelligence ambiante0
Classification with the matrix-variate-t distribution0
Failure Analysis on Multivariate Time-series Data given Uncertain Labels0
Analysis and development of an automatic eCall for motorcycles: a one-class cepstrum approach0
Towards Learning Universal, Regional, and Local Hydrological Behaviors via Machine-Learning Applied to Large-Sample DatasetsCode0
MIMIC-Extract: A Data Extraction, Preprocessing, and Representation Pipeline for MIMIC-IIICode0
A hybrid method of Exponential Smoothing and Recurrent Neural Networks for time series forecastingCode0
Convolutional Reservoir Computing for World ModelsCode0
An Adaptive Approach for Anomaly Detector Selection and Fine-Tuning in Time Series0
Can Machine Learning Identify Governing Laws For Dynamics in Complex Engineered Systems ? : A Study in Chemical Engineering0
Clustering Activity-Travel Behavior Time Series using Topological Data Analysis0
Remaining Useful Lifetime Prediction via Deep Domain Adaptation0
Meta-descent for Online, Continual Prediction0
End-To-End Prediction of Emotion From Heartbeat Data Collected by a Consumer Fitness Tracker0
Quant GANs: Deep Generation of Financial Time Series0
Deciphering Dynamical Nonlinearities in Short Time Series Using Recurrent Neural Networks0
Dynamical Systems as Temporal Feature Spaces0
Quick, Stat!: A Statistical Analysis of the Quick, Draw! Dataset0
An Artificial Spiking Quantum Neuron0
Bayesian Synthesis of Probabilistic Programs for Automatic Data Modeling0
The Use of Gaussian Processes in System Identification0
A machine learning framework for computationally expensive transient modelsCode0
Automated Real-time Anomaly Detection in Human Trajectories using Sequence to Sequence Networks0
Activity2Vec: Learning ADL Embeddings from Sensor Data with a Sequence-to-Sequence ModelCode0
General Evaluation for Instruction Conditioned Navigation using Dynamic Time WarpingCode1
Change point detection for graphical models in the presence of missing valuesCode0
Forecasting Time Series with VARMA Recursions on Graphs0
Time series cluster kernels to exploit informative missingness and incomplete label information0
Fetal Pose Estimation in Volumetric MRI using a 3D Convolution Neural Network0
Kernel Hypothesis Testing with Set-valued Data0
Using Temporal and Topological Features for Intrusion Detection in Operational Networks0
GP-VAE: Deep Probabilistic Time Series ImputationCode0
Non-technical Loss Detection with Statistical Profile Images Based on Semi-supervised Learning0
Routine Modeling with Time Series Metric Learning0
Latent ODEs for Irregularly-Sampled Time SeriesCode1
Attending to Emotional NarrativesCode0
Fast ES-RNN: A GPU Implementation of the ES-RNN AlgorithmCode0
Takens-inspired neuromorphic processor: a downsizing tool for random recurrent neural networks via feature extraction0
A Quantum Field Theory of Representation Learning0
Financial Time Series Data Processing for Machine LearningCode1
VELC: A New Variational AutoEncoder Based Model for Time Series Anomaly DetectionCode0
Action Prediction in Humans and Robots0
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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