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

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Showing 551–600 of 6748 papers

TitleStatusHype
Coincident Learning for Unsupervised Anomaly Detection—0
Neural Continuous-Discrete State Space Models for Irregularly-Sampled Time SeriesCode1
Motion ID: Human Authentication Approach—0
Partial Mobilization: Tracking Multilingual Information Flows Amongst Russian Media Outlets and Telegram—0
Recursive deep learning framework for forecasting the decadal world economic outlookCode0
Salesforce CausalAI Library: A Fast and Scalable Framework for Causal Analysis of Time Series and Tabular DataCode2
Context-specific kernel-based hidden Markov model for time series analysisCode0
Lightweight Neural Architecture Search for Temporal Convolutional Networks at the EdgeCode1
WEASEL 2.0 -- A Random Dilated Dictionary Transform for Fast, Accurate and Memory Constrained Time Series ClassificationCode1
Parameterizing the cost function of Dynamic Time Warping with application to time series classification—0
Neuronal architecture extracts statistical temporal patternsCode0
Multi-view Kernel PCA for Time series Forecasting—0
Flexible conditional density estimation for time series—0
Chemical Integration of ODEs using Idealized Abstract SolutionsCode0
A Framework for Evaluating the Impact of Food Security Scenarios—0
ECGAN: Self-supervised generative adversarial network for electrocardiography—0
Learning Reservoir Dynamics with Temporal Self-Modulation—0
LSTM and CNN application for core-collapse supernova search in gravitational wave real data—0
StockEmotions: Discover Investor Emotions for Financial Sentiment Analysis and Multivariate Time SeriesCode1
Prompt Federated Learning for Weather Forecasting: Toward Foundation Models on Meteorological DataCode1
Estimation of Sea State Parameters from Ship Motion Responses Using Attention-based Neural Networks—0
Ti-MAE: Self-Supervised Masked Time Series AutoencodersCode1
The Conditional Cauchy-Schwarz Divergence with Applications to Time-Series Data and Sequential Decision MakingCode0
Interpretable Classification of Early Stage Parkinson's Disease from EEG—0
AI enabled RPM for Mental Health Facility—0
Regular Time-series Generation using SGM—0
Dataset Bias in Human Activity Recognition—0
PDFormer: Propagation Delay-Aware Dynamic Long-Range Transformer for Traffic Flow PredictionCode2
Diffusion-based Conditional ECG Generation with Structured State Space ModelsCode1
Synthcity: facilitating innovative use cases of synthetic data in different data modalitiesCode2
Deep Learning Enables Reduced Gadolinium Dose for Contrast-Enhanced Blood-Brain Barrier Opening—0
Leveraging Vision-Language Models for Granular Market Change Prediction—0
Planning of Fast Charging Infrastructure for Electric Vehicles in a Distribution System and Prediction of Dynamic Price—0
Probabilistic Traffic Forecasting with Dynamic RegressionCode0
ActSafe: Predicting Violations of Medical Temporal Constraints for Medication Adherence—0
Predictive Modeling of Coronal Hole Areas Using Long Short-Term Memory Networks—0
Temporal-lobe Epilepsy: Harmonic and Anharmonic Periodicity in Microeletrode Voltage—0
Sensor data-driven analysis for identification of causal relationships between exposure to air pollution and respiratory rate in asthmatics—0
A Transformer-based Diffusion Probabilistic Model for Heart Rate and Blood Pressure Forecasting in Intensive Care UnitCode1
Causal Recurrent Variational Autoencoder for Medical Time Series GenerationCode1
Robust M-Estimation for Additive Single-Index Cointegrating Time Series Models—0
Efficient anomaly detection method for rooftop PV systems using big data and permutation entropy—0
Ordinal methods for a characterization of evolving functional brain networks—0
Building a Fuel Moisture Model for the Coupled Fire-Atmosphere Model WRF-SFIRE from Data: From Kalman Filters to Recurrent Neural Networks—0
LB-SimTSC: An Efficient Similarity-Aware Graph Neural Network for Semi-Supervised Time Series Classification—0
Neural Spline Search for Quantile Probabilistic Modeling—0
Unsupervised Driving Event Discovery Based on Vehicle CAN-data—0
A Novel Framework for Handling Sparse Data in Traffic Forecast—0
ViTs for SITS: Vision Transformers for Satellite Image Time SeriesCode2
Persistence-Based Discretization for Learning Discrete Event Systems from Time Series—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