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 60516100 of 6748 papers

TitleStatusHype
Deep Neural Dynamic Bayesian Networks applied to EEG sleep spindles modelingCode0
Learning from the past, predicting the statistics for the future, learning an evolving systemCode0
On the Reconstruction Risk of Convolutional Sparse Dictionary LearningCode0
GP-ConvCNP: Better Generalization for Convolutional Conditional Neural Processes on Time Series DataCode0
The UEA multivariate time series classification archive, 2018Code0
Global Models for Time Series Forecasting: A Simulation StudyCode0
Gesture Recognition in RGB Videos UsingHuman Body Keypoints and Dynamic Time WarpingCode0
Benchmarking optimality of time series classification methods in distinguishing diffusionsCode0
On the separation of shape and temporal patterns in time series -Application to signature authentication-Code0
Twitter mood predicts the stock marketCode0
On the Soundness of XAI in Prognostics and Health Management (PHM)Code0
An ensemble neural network approach to forecast Dengue outbreak based on climatic conditionCode0
Coronavirus Optimization Algorithm: A bioinspired metaheuristic based on the COVID-19 propagation modelCode0
Learning Informative Representation for Fairness-aware Multivariate Time-series Forecasting: A Group-based PerspectiveCode0
Learning interaction rules from multi-animal trajectories via augmented behavioral modelsCode0
ST-LSTM: A Deep Learning Approach Combined Spatio-Temporal Features for Short-TermCode0
The Utility of Hyperplane Angle Metric in Detecting Financial Concept DriftCode0
Toward Asymptotic Optimality: Sequential Unsupervised Regression of Density Ratio for Early ClassificationCode0
Identifying Latent Stochastic Differential EquationsCode0
Stochastic embeddings of dynamical phenomena through variational autoencodersCode0
Geodesic Density Regression for Correcting 4DCT Pulmonary Respiratory Motion ArtifactsCode0
Robust Lane Detection from Continuous Driving Scenes Using Deep Neural NetworksCode0
Generative Optimization Networks for Memory Efficient Data GenerationCode0
Learning low-frequency temporal patterns for quantitative tradingCode0
Stochastic Gradient MCMC for Nonlinear State Space ModelsCode0
Stochastic Gradient MCMC for State Space ModelsCode0
The Wasserstein-Fourier Distance for Stationary Time SeriesCode0
Data-Driven Modeling of Noise Time Series with Convolutional Generative Adversarial NetworksCode0
An Empirical Evaluation of Multivariate Time Series Classification with Input Transformation across Different DimensionsCode0
Warped Dynamic Linear Models for Time Series of CountsCode0
Think Globally, Act Locally: A Deep Neural Network Approach to High-Dimensional Time Series ForecastingCode0
Detecting Distributional Differences in Labeled Sequence Data with Application to Tropical Cyclone Satellite ImageryCode0
On Transfer Learning For Chatter Detection in Turning Using Wavelet Packet Transform and Empirical Mode DecompositionCode0
Detecting and Explaining Causes From Text For a Time Series EventCode0
Learning Physical Concepts in Cyber-Physical Systems: A Case StudyCode0
Open-domain Event Extraction and Embedding for Natural Gas Market PredictionCode0
Learning Predictive Leading Indicators for Forecasting Time Series Systems with Unknown Clusters of Forecast TasksCode0
Variational Encoding of Complex DynamicsCode0
Opinion Prediction with User FingerprintingCode0
Learning Procedural Abstractions and Evaluating Discrete Latent Temporal StructureCode0
Towards Learning Universal, Regional, and Local Hydrological Behaviors via Machine-Learning Applied to Large-Sample DatasetsCode0
Optimal activity and battery scheduling algorithm using load and solar generation forecastCode0
Stochastic Weight Matrix-based Regularization Methods for Deep Neural NetworksCode0
Robust Parameter-Free Season Length Detection in Time SeriesCode0
StockBot: Using LSTMs to Predict Stock PricesCode0
Learning Representations for Time Series ClusteringCode0
Learning Representations from EEG with Deep Recurrent-Convolutional Neural NetworksCode0
CORAD: Correlation-Aware Compression of Massive Time Series using Sparse Dictionary CodingCode0
Derivative Delay Embedding: Online Modeling of Streaming Time SeriesCode0
COPER: Continuous Patient State PerceiverCode0
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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